Showing 165 publications by Vicente Grau Colomer
Correction: Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
Ryou H, Sirinukunwattana K, Aberdeen A, Grindstaff G, Stolz BJ et al. (2023), Leukemia
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
Ryou H, Sirinukunwattana K, Aberdeen A, Grindstaff G, Stolz BJ et al. (2022), Leukemia
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
Harrington H, Ryou H, Sirinukunwattana K, Aberdeen A, Grindstaff G et al. (2022), Leukemia
RFID analysis of the complexity of cellular pathology workflow—An opportunity for digital pathology
Browning L, White K, Siiankoski D, Colling R, Roskell D et al. (2022), Frontiers in Medicine, 9
BibTeX
@article{rfidanalysisoft-2022/8,
title={RFID analysis of the complexity of cellular pathology workflow—An opportunity for digital pathology},
author={Browning L, White K, Siiankoski D, Colling R, Roskell D et al.},
journal={Frontiers in Medicine},
volume={9},
number={933933},
publisher={Frontiers Media},
year = "2022"
}
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy.
Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J (2022), Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 101, 102112
BibTeX
@article{multiclassmotio-2022/8,
title={Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy.},
author={Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J},
journal={Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society},
volume={101},
pages={102112},
year = "2022"
}
Patch-level instance-group discrimination with pretext-invariant learning for colitis scoring
Xu Z, Ali S, Gupta S, Leedham S, East JE et al. (2022)
BibTeX
@misc{patchlevelinsta-2022/7,
title={Patch-level instance-group discrimination with pretext-invariant
learning for colitis scoring},
author={Xu Z, Ali S, Gupta S, Leedham S, East JE et al.},
year = "2022"
}
Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region
Browning L, Winter L, Cooper RA, Ghosh A, Dytor T et al. (2022), Journal of Clinical Pathology
BibTeX
@article{impactofthetran-2022/7,
title={Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region},
author={Browning L, Winter L, Cooper RA, Ghosh A, Dytor T et al.},
journal={Journal of Clinical Pathology},
publisher={BMJ Publishing Group},
year = "2022"
}
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples.
Martin NG, Malacrino S, Wojciechowska M, Campo L, Jones H et al. (2022), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022, 3063-3067
BibTeX
@article{agraphbasedneur-2022/7,
title={A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples.},
author={Martin NG, Malacrino S, Wojciechowska M, Campo L, Jones H et al.},
journal={Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
volume={2022},
pages={3063-3067},
year = "2022"
}
Multi-Scale Graphical Representation of Cell Environment.
Theissen H, Chakraborty T, Malacrino S, Royston D & Rittscher J (2022), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2022, 3522-3525
BibTeX
@article{multiscalegraph-2022/7,
title={Multi-Scale Graphical Representation of Cell Environment.},
author={Theissen H, Chakraborty T, Malacrino S, Royston D & Rittscher J},
journal={Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
volume={2022},
pages={3522-3525},
year = "2022"
}
Predicting Clinical Endpoints and Visual Changes with Quality-Weighted Tissue-based Renal Histological Features
Tam KH, Soares M, Kers J, Sharples E, Ploeg R et al. (2022)
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.
Tomar NK, Jha D, Riegler MA, Johansen HD, Johansen D et al. (2022), IEEE transactions on neural networks and learning systems, PP
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Ali S, Ghatwary N, Jha D, Isik-Polat E, Polat G et al. (2022)
BibTeX
@misc{assessinggenera-2022/2,
title={Assessing generalisability of deep learning-based polyp detection and
segmentation methods through a computer vision challenge},
author={Ali S, Ghatwary N, Jha D, Isik-Polat E, Polat G et al.},
year = "2022"
}
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples
Martin NG, Malacrino S, Wojciechowska M, Campo L, Jones H et al. (2022)
BibTeX
@misc{agraphbasedneur-2022/2,
title={A Graph Based Neural Network Approach to Immune Profiling of Multiplexed
Tissue Samples},
author={Martin NG, Malacrino S, Wojciechowska M, Campo L, Jones H et al.},
year = "2022"
}
Additive Angular Margin Loss and Model Scaling Network for Optimised Colitis Scoring
Xu Z, Ali S, East J & Rittscher J (2022), Proceedings - International Symposium on Biomedical Imaging, 2022-March
Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy
Han H, Dmitrieva M, Sauer A, Tam KH & Rittscher J (2022), IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2022-June, 1873-1882
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning
Hu Y, Sirinukunwattana K, Gaitskell K, Wood R, Verrill C et al. (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13432 LNCS, 130-139
Profiling DNA Damage in 3D Histology Samples
delas Peñas KE, Haeusler R, Feng S, Magidson V, Dmitrieva M et al. (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13578 LNCS, 84-93
Self-supervised Approach for a Fully Assistive Esophageal Surveillance: Quality, Anatomy and Neoplasia Guidance
Xu Z, Ali S, Celik N, Bailey A, Braden B et al. (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13581 LNCS, 14-23
Active Data Enrichment by Learning What to Annotate in Digital Pathology
Batchkala G, Chakraborti T, McCole M, Gleeson F & Rittscher J (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13581 LNCS, 118-127
UNet-eVAE: Iterative Refinement Using VAE Embodied Learning for Endoscopic Image Segmentation
Gupta S, Ali S, Xu Z, Bhattarai B, Turney B et al. (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13583 LNCS, 161-170
Patch-Level Instance-Group Discrimination with Pretext-Invariant Learning for Colitis Scoring
Xu Z, Ali S, Gupta S, Leedham S, East JE et al. (2022), 101-110
Digital pathology transformation in a supraregional germ cell tumour network
Colling R, Protheroe A, Macpherson R, Tuthill M, Redgwell J et al. (2021), Diagnostics, 11(12)
Learning Cellular Phenotypes through Supervision.
Theissen H, Chakraborti T, Malacrino S, Sirinukunwattana K, Royston D et al. (2021), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 3592-3595
Automated Annotator: Capturing Expert Knowledge for Free.
Elmes S, Chakraborti T, Fan M, Uhlig H & Rittscher J (2021), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 2664-2667
DEEP-LEARNING BASED PREDICTION OF CLINICAL ENDPOINTS IN RENAL PRE-IMPLANTATION BIOPSIES USING SLIDE-LEVEL LABELS
Tam KH, Soares MF, Sharples E, Kaisar M, Ploeg R et al. (2021), TRANSPLANT INTERNATIONAL, 34, 159-160
BibTeX
@inproceedings{deeplearningbas-2021/8,
title={DEEP-LEARNING BASED PREDICTION OF CLINICAL ENDPOINTS IN RENAL PRE-IMPLANTATION BIOPSIES USING SLIDE-LEVEL LABELS},
author={Tam KH, Soares MF, Sharples E, Kaisar M, Ploeg R et al.},
pages={159-160},
year = "2021"
}
Transcriptome and genome evolution during HER2-amplified breast neoplasia
Lu P, Foley J, Zhu C, McNamara K, Sirinukunwattana K et al. (2021), Breast Cancer Research, 23
Tumour irradiation combined with vascular-targeted photodynamic therapy enhances anti-tumour effects in preclinical prostate cancer
Sjoberg H, Philippou Y, Tullis I, Bridges E, Chatrian A et al. (2021), British Journal of Cancer, 125(2021), 534-546
BibTeX
@article{tumourirradiati-2021/6,
title={Tumour irradiation combined with vascular-targeted photodynamic therapy enhances anti-tumour effects in preclinical prostate cancer},
author={Sjoberg H, Philippou Y, Tullis I, Bridges E, Chatrian A et al.},
journal={British Journal of Cancer},
volume={125},
pages={534-546},
publisher={Springer Nature},
year = "2021"
}
A pilot study on automatic three-dimensional quantification of Barrett's esophagus for risk stratification and therapy monitoring
Ali S, Bailey A, Ash S, Haghighat M, Leedham SJ et al. (2021), Gastroenterology, 161(3), 865-878
BibTeX
@article{apilotstudyonau-2021/6,
title={A pilot study on automatic three-dimensional quantification of Barrett's esophagus for risk stratification and therapy monitoring},
author={Ali S, Bailey A, Ash S, Haghighat M, Leedham SJ et al.},
journal={Gastroenterology},
volume={161},
pages={865-878},
publisher={Elsevier},
year = "2021"
}
PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
Ali S, Jha D, Ghatwary N, Realdon S, Cannizzaro R et al. (2021)
BibTeX
@misc{polypgenamultic-2021/6,
title={PolypGen: A multi-center polyp detection and segmentation dataset for
generalisability assessment},
author={Ali S, Jha D, Ghatwary N, Realdon S, Cannizzaro R et al.},
year = "2021"
}
Phenotyping of <i>Klf14</i> mouse white adipose tissue enabled by whole slide segmentation with deep neural networks
Casero R, Westerberg H, Horner N, Yon M, Aberdeen A et al. (2021)
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.
Ghatwary N, Bano S, Polat G, Temizel A, Krenzer A et al. (2021), Medical image analysis, 70, 102002
BibTeX
@article{deeplearningfor-2021/5,
title={Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.},
author={Ghatwary N, Bano S, Polat G, Temizel A, Krenzer A et al.},
journal={Medical image analysis},
volume={70},
number={ARTN 102002},
pages={102002},
publisher={Elsevier BV},
year = "2021"
}
Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies
Colling R, Browning L, Alham NK, Sirinukunwattana K, Malacrino S et al. (2021), Modern Pathology, 34, 1780-1794
BibTeX
@article{artificialintel-2021/5,
title={Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies},
author={Colling R, Browning L, Alham NK, Sirinukunwattana K, Malacrino S et al.},
journal={Modern Pathology},
volume={34},
pages={1780-1794},
publisher={Springer Nature},
year = "2021"
}
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy
Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J (2021)
BibTeX
@misc{multiclassmotio-2021/4,
title={Multi-class motion-based semantic segmentation for ureteroscopy and
laser lithotripsy},
author={Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J},
year = "2021"
}
Real-time polyp detection, localization and segmentation in colonoscopy using deep learning
Jha D, Ali S, Tomar NK, Johansen HD, Johansen D et al. (2021), IEEE Access, 9, 40496-40510
The potential of artificial intelligence to detect lymphovascular invasion in testicular cancer
Ghosh A, Sirinukunwattana K, Khalid Alham N, Browning L, Colling R et al. (2021), Cancers, 13(6)
BibTeX
@article{thepotentialofa-2021/3,
title={The potential of artificial intelligence to detect lymphovascular invasion in testicular cancer},
author={Ghosh A, Sirinukunwattana K, Khalid Alham N, Browning L, Colling R et al.},
journal={Cancers},
volume={13},
number={1325},
publisher={MDPI},
year = "2021"
}
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
Tomar NK, Jha D, Riegler MA, Johansen HD, Johansen D et al. (2021)
BibTeX
@misc{fanetafeedbacka-2021/3,
title={FANet: A Feedback Attention Network for Improved Biomedical Image
Segmentation},
author={Tomar NK, Jha D, Riegler MA, Johansen HD, Johansen D et al.},
year = "2021"
}
Improved Artifact Detection in Endoscopy Imaging Through Profile Pruning
Xu Z, Ali S, Gupta S, Celik N & Rittscher J (2021), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12722 LNCS, 87-97
Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detection
Chowdhury T, Bajwa ARS, Chakraborti T, Rittscher J & Pal U (2021), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12722 LNCS, 3-17
Contrastive Representations for Continual Learning of Fine-Grained Histology Images
Chakraborti T, Gleeson F & Rittscher J (2021), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12966 LNCS, 1-9
TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data.
Reina F, Wigg JMA, Dmitrieva M, Vogler B, Lefebvre J et al. (2021), F1000Research, 10, 838
EndoUDA: A Modality Independent Segmentation Approach for Endoscopy Imaging
Celik N, Ali S, Gupta S, Braden B & Rittscher J (2021), MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT III, 12903, 303-312
Early Detection of Liver Fibrosis Using Graph Convolutional Networks
Wojciechowska M, Malacrino S, Martin NG, Fehri H & Rittscher J (2021), MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT VIII, 12908, 217-226
Unsupervised Adversarial Domain Adaptation For Barrett's Segmentation
Celik N, Gupta S, Ali S & Rittscher J (2020)
BibTeX
@misc{unsupervisedadv-2020/12,
title={Unsupervised Adversarial Domain Adaptation For Barrett's Segmentation},
author={Celik N, Gupta S, Ali S & Rittscher J},
year = "2020"
}
A deep learning framework for quality assessment and restoration in video endoscopy
ALI S, ZHOU FY, Bailey A, Braden B, East J et al. (2020), Medical Image Analysis
BibTeX
@article{adeeplearningfr-2020/11,
title={A deep learning framework for quality assessment and restoration in
video endoscopy},
author={ALI S, ZHOU FY, Bailey A, Braden B, East J et al.},
journal={Medical Image Analysis},
publisher={Elsevier},
year = "2020"
}
Artificial intelligence-driven real-time 3D surface quantification of Barrett's oesophagus for risk stratification and therapeutic response monitoring
Ali S, Bailey A, East JE, Leedham SJ, Haghighat M et al. (2020), medRxiv
Artificial intelligence for colonoscopic polyp detection: High performance versus human nature
East JE & Rittscher J (2020), Journal of Gastroenterology and Hepatology, 35(10), 1663-1664
A translational pathway of deep learning methods in GastroIntestinal Endoscopy
ALI S & RITTSCHER J (2020)
BibTeX
@misc{atranslationalp-2020/10,
title={A translational pathway of deep learning methods in GastroIntestinal Endoscopy},
author={ALI S & RITTSCHER J},
year = "2020"
}
Detailed Molecular and Immune Marker Profiling of Archival Prostate Cancer Samples Reveals an Inverse Association between TMPRSS2:ERG Fusion Status and Immune Cell Infiltration (vol 22, pg 652, 2020)
Rao SR, Alham NK, Upton E, McIntyre S, Bryant RJ et al. (2020), JOURNAL OF MOLECULAR DIAGNOSTICS, 22(9), 1216-1216
BibTeX
@article{detailedmolecul-2020/9,
title={Detailed Molecular and Immune Marker Profiling of Archival Prostate Cancer Samples Reveals an Inverse Association between TMPRSS2:ERG Fusion Status and Immune Cell Infiltration (vol 22, pg 652, 2020)},
author={Rao SR, Alham NK, Upton E, McIntyre S, Bryant RJ et al.},
journal={JOURNAL OF MOLECULAR DIAGNOSTICS},
volume={22},
pages={1216-1216},
year = "2020"
}
DeepScratch: single-cell based topological metrics of scratch wound assays
Javer Godinez A, Rittscher J & Sailem H (2020), Computational and Structural Biotechnology Journal, 18, 2501-2509
BibTeX
@article{deepscratchsing-2020/8,
title={DeepScratch: single-cell based topological metrics of scratch wound assays},
author={Javer Godinez A, Rittscher J & Sailem H},
journal={Computational and Structural Biotechnology Journal},
volume={18},
pages={2501-2509},
publisher={Elsevier},
year = "2020"
}
Role of digital pathology in diagnostic histopathology in the response to COVID-19: results from a survey of experience in a UK tertiary referral hospital
Browning L, Fryer E, Roskell D, White K, Colling R et al. (2020), Journal of Clinical Pathology, 74(2), 129-132
BibTeX
@article{roleofdigitalpa-2020/7,
title={Role of digital pathology in diagnostic histopathology in the response to COVID-19: results from a survey of experience in a UK tertiary referral hospital},
author={Browning L, Fryer E, Roskell D, White K, Colling R et al.},
journal={Journal of Clinical Pathology},
volume={74},
pages={129-132},
publisher={BMJ},
year = "2020"
}
Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning
Sirinukunwattana K, Domingo-Villanueva E, Richman S, Blake A, Verrill C et al. (2020), Gut, 70(3), 544-554
BibTeX
@article{imagebasedconse-2020/7,
title={Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning},
author={Sirinukunwattana K, Domingo-Villanueva E, Richman S, Blake A, Verrill C et al.},
journal={Gut},
volume={70},
pages={544-554},
publisher={BMJ Publishing Group},
year = "2020"
}
Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE consortium perspective
Browning L, Colling R, Rakha E, Rajpoot N, Rittscher J et al. (2020), Journal of Clinical Pathology, 74(7), 443-447
BibTeX
@article{digitalpatholog-2020/7,
title={Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE consortium perspective},
author={Browning L, Colling R, Rakha E, Rajpoot N, Rittscher J et al.},
journal={Journal of Clinical Pathology},
volume={74},
pages={443-447},
publisher={BMJ Publishing Group},
year = "2020"
}
Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients
Sirinukunwattana K, Aberdeen A, Theissen H, Sousos N, Psaila B et al. (2020), Blood Advances, 4(14), 3284-3294
BibTeX
@article{artificialintel-2020/7,
title={Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients},
author={Sirinukunwattana K, Aberdeen A, Theissen H, Sousos N, Psaila B et al.},
journal={Blood Advances},
volume={4},
pages={3284-3294},
publisher={American Society of Hematology},
year = "2020"
}
Multi-scale sensorless adaptive optics: application to stimulated emission depletion microscopy
Antonello J, Barbotin A, Chong EZ, Rittscher J & Booth M (2020), Optics Express, 28(11), 16749-16763
BibTeX
@article{multiscalesenso-2020/5,
title={Multi-scale sensorless adaptive optics: application to stimulated emission depletion microscopy},
author={Antonello J, Barbotin A, Chong EZ, Rittscher J & Booth M},
journal={Optics Express},
volume={28},
pages={16749-16763},
publisher={Optical Society of America},
year = "2020"
}
MI-UNet: improved segmentation in ureteroscopy
Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J (2020), Proceedings - International Symposium on Biomedical Imaging, 2020-April, 212-216
Short trajectory segmentation with 1D UNET Framework: application to secretory vesicle dynamics
Dmitrieva M, Lefebvre J, delas Peñas K, Zenner H, Richens J et al. (2020), 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 891-894
BibTeX
@inproceedings{shorttrajectory-2020/5,
title={Short trajectory segmentation with 1D UNET Framework: application to secretory vesicle dynamics},
author={Dmitrieva M, Lefebvre J, delas Peñas K, Zenner H, Richens J et al.},
booktitle={2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)},
pages={891-894},
year = "2020"
}
Extracting axial depth and trajectory trend using astigmatism, Gaussian fitting, and CNNs for protein tracking
Delas Penas K, Dmitrieva M, Lefebvre J, Zenner H, Allgeyer E et al. (2020), 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1634-1637
BibTeX
@inproceedings{extractingaxial-2020/4,
title={Extracting axial depth and trajectory trend using astigmatism, Gaussian fitting, and CNNs for protein tracking},
author={Delas Penas K, Dmitrieva M, Lefebvre J, Zenner H, Allgeyer E et al.},
booktitle={International Symposium on Biomedical Imaging},
pages={1634-1637},
year = "2020"
}
Single-Molecule Localization Microscopy Reconstruction Using Noise2Noise for Super-Resolution Imaging of Actin Filaments
Lefebvre J, Javer A, Dmitrieva M, Rittscher J, Lewkow B et al. (2020), Proceedings - International Symposium on Biomedical Imaging, 2020-April, 1596-1599
BibTeX
@inproceedings{singlemoleculel-2020/4,
title={Single-Molecule Localization Microscopy Reconstruction Using Noise2Noise for Super-Resolution Imaging of Actin Filaments},
author={Lefebvre J, Javer A, Dmitrieva M, Rittscher J, Lewkow B et al.},
booktitle={IEEE International Symposium on Biomedical Imaging (ISBI'20)},
pages={1596-1599},
year = "2020"
}
Fine-Grained Multi-Instance Classification in Microscopy Through Deep Attention
Fan M, Chakraborti T, Chang E, Xu Y & Rittscher J (2020), Proceedings - International Symposium on Biomedical Imaging, 2020-April, 169-173
BibTeX
@inproceedings{finegrainedmult-2020/4,
title={Fine-Grained Multi-Instance Classification in Microscopy Through Deep Attention},
author={Fan M, Chakraborti T, Chang E, Xu Y & Rittscher J},
booktitle={IEEE International Symposium on Biomedical Imaging (ISBI'20)},
pages={169-173},
year = "2020"
}
Endoscopy disease detection challenge 2020
Ali S, Ghatwary N, Braden B, Lamarque D, Bailey A et al. (2020)
BibTeX
@misc{endoscopydiseas-2020/3,
title={Endoscopy disease detection challenge 2020},
author={Ali S, Ghatwary N, Braden B, Lamarque D, Bailey A et al.},
year = "2020"
}
KCML: a machine‐learning framework for inference of multi‐scale gene functions from genetic perturbation screens
Sailem HZ, Rittscher J & Pelkmans L (2020), Molecular Systems Biology, 16(3)
BibTeX
@article{kcmlamachinelea-2020/3,
title={KCML: a machine‐learning framework for inference of multi‐scale gene functions from genetic perturbation screens},
author={Sailem HZ, Rittscher J & Pelkmans L},
journal={Molecular Systems Biology},
volume={16},
number={e9083},
publisher={Wiley Open Access },
year = "2020"
}
Additive angular margin for few shot learning to classify clinical endoscopy images
Ali S, Bhattarai B, Kim T-K & Rittscher J (2020), arXiv
BibTeX
@inproceedings{additiveangular-2020/3,
title={Additive angular margin for few shot learning to classify clinical endoscopy images},
author={Ali S, Bhattarai B, Kim T-K & Rittscher J},
year = "2020"
}
Detailed molecular and immune marker profiling of archival prostate cancer samples reveals an inverse association between TMPRSS2:ERG fusion status and immune cell infiltration
Rao SR, Alham NK, Upton E, McIntyre S, Bryant RJ et al. (2020), Journal of Molecular Diagnostics, 22(5), 652-669
BibTeX
@article{detailedmolecul-2020/3,
title={Detailed molecular and immune marker profiling of archival prostate cancer samples reveals an inverse association between TMPRSS2:ERG fusion status and immune cell infiltration},
author={Rao SR, Alham NK, Upton E, McIntyre S, Bryant RJ et al.},
journal={Journal of Molecular Diagnostics},
volume={22},
pages={652-669},
publisher={Elsevier},
year = "2020"
}
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Ali S, Braden B, Bailey A, Yang S, Zhang P et al. (2020), Scientific reports, 10(1), 2748
BibTeX
@article{anobjectivecomp-2020/2,
title={An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy},
author={Ali S, Braden B, Bailey A, Yang S, Zhang P et al.},
journal={Scientific reports},
volume={10},
pages={2748},
publisher={Springer Nature},
year = "2020"
}
Motion induced segmentation of stone fragments in ureteroscopy video
Gupta S, Ali S, Goldsmith L, Turney B & Rittscher J (2020), Proceedings of SPIE - The International Society for Optical Engineering, 11315
Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.
Shah M, Roomans Ledo A & Rittscher J (2020), Acta ophthalmologica
Proceedings of the ENDOCV 2020 2nd international workshop and challenge on computer vision in endoscopy
Ali S, Daul C, Rittscher J, Stoyanov D & Grisan E (2020), CEUR Workshop Proceedings, 2595, 1-7
BibTeX
@inproceedings{proceedingsofth-2020/1,
title={Proceedings of the ENDOCV 2020 2nd international workshop and challenge on computer vision in endoscopy},
author={Ali S, Daul C, Rittscher J, Stoyanov D & Grisan E},
pages={1-7},
year = "2020"
}
DeepSplit: Segmentation of Microscopy Images Using Multi-task Convolutional Networks
Torr A, Basaran D, Sero J, Rittscher J & Sailem H (2020), Communications in Computer and Information Science, 1248 CCIS, 155-167
Improving Pathological Distribution Measurements with Bayesian Uncertainty
Tam KH, Sirinukunwattana K, Soares MF, Kaisar M, Ploeg R et al. (2020), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12443 LNCS, 61-70
Implementation of digital pathology into diagnostic practice: perceptions and opinions of histopathology trainees and implications for training
Browning L, Colling R, Rittscher J, Winter L, McEntyre N et al. (2019), Journal of Clinical Pathology
BibTeX
@article{implementationo-2019/10,
title={Implementation of digital pathology into diagnostic practice: perceptions and opinions of histopathology trainees and implications for training},
author={Browning L, Colling R, Rittscher J, Winter L, McEntyre N et al.},
journal={Journal of Clinical Pathology},
publisher={BMJ Publishing Group},
year = "2019"
}
Semantic filtering through deep source separation on microscopy images
Javer A & Rittscher J (2019), Machine Learning in Medical Imaging, 11861, 498-506
Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping
Ali S & Rittscher J (2019), Machine Learning in Medical Imaging, 11861, 489-497
Protein Tracking by CNN-Based Candidate Pruning and Two-Step Linking with Bayesian Network
Dmitrieva M, Zenner HL, Richens J, Johnston DS & Rittscher J (2019), IEEE International Workshop on Machine Learning for Signal Processing, MLSP, 2019-October
BibTeX
@inproceedings{proteintracking-2019/10,
title={Protein Tracking by CNN-Based Candidate Pruning and Two-Step Linking with Bayesian Network},
author={Dmitrieva M, Zenner HL, Richens J, Johnston DS & Rittscher J},
booktitle={2019 IIEEE 29th International Workshop on Machine Learning for Signal Processing},
year = "2019"
}
Moving to a Digital Pathology Supraregional Germ Cell Tumour Service
Colling RT, White K, Rittscher J, Roskell D, Hemsworth H et al. (2019), JOURNAL OF PATHOLOGY, 249, S29-S29
BibTeX
@inproceedings{movingtoadigita-2019/9,
title={Moving to a Digital Pathology Supraregional Germ Cell Tumour Service},
author={Colling RT, White K, Rittscher J, Roskell D, Hemsworth H et al.},
pages={S29-S29},
year = "2019"
}
Characterization of Biological Motion Using Motion Sensing Superpixels.
Zhou FY, Ruiz-Puig C, Owen RP, White MJ, Rittscher J et al. (2019), Bio-protocol, 9(18), e3365
Ink removal from histopathology whole slide images by combining classification, detection and image generation models
Ali S, Alham NK, Verrill C & Rittscher J (2019), 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 928-932
BibTeX
@article{inkremovalfromh-2019/7,
title={Ink removal from histopathology whole slide images by combining classification, detection and image generation models},
author={Ali S, Alham NK, Verrill C & Rittscher J},
journal={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},
pages={928-932},
publisher={IEEE},
year = "2019"
}
Efficient video indexing for monitoring disease activity and progression in the upper gastrointestinal tract
Ali S & Rittscher J (2019), 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)
Correction: Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes.
Zhou FY, Ruiz-Puig C, Owen RP, White MJ, Rittscher J et al. (2019), eLife, 8
Capturing variations in nuclear phenotypes
Raman S, Singh S, Pecot T, Caserta E, Huang K et al. (2019), Journal of Computational Science , 36
Towards the identification of histology based subtypes in prostate cancer
Chatrian A, Sirinukunwattana K, Verrill C & Rittscher J (2019), 2019 IEEE 16th International Symposium On Biomedical Imaging (ISBI 2019), 948-952
BibTeX
@inproceedings{towardstheident-2019/7,
title={Towards the identification of histology based subtypes in prostate cancer},
author={Chatrian A, Sirinukunwattana K, Verrill C & Rittscher J},
booktitle={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},
pages={948-952},
year = "2019"
}
Endoscopy artifact detection (EAD 2019) challenge dataset
Ali S, Zhou F, Daul C, Braden B, Bailey A et al. (2019)
BibTeX
@misc{endoscopyartifa-2019/5,
title={Endoscopy artifact detection (EAD 2019) challenge dataset},
author={Ali S, Zhou F, Daul C, Braden B, Bailey A et al.},
year = "2019"
}
Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning
RITTSCHER J, SIRINUKUNWATTANA K, Domingo E, Richman S, Redmond K et al. (2019)
Motion Sensing Superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes
Zhou F, Ruiz-Puig C, Owen R, White M, Rittscher J et al. (2019), eLife, 8, e40162
BibTeX
@article{motionsensingsu-2019/2,
title={Motion Sensing Superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes},
author={Zhou F, Ruiz-Puig C, Owen R, White M, Rittscher J et al.},
journal={eLife},
volume={8},
pages={e40162},
publisher={eLife Sciences Publications},
year = "2019"
}
The use of digital pathology and image analysis in clinical trials
Pell R, Oien K, Robinson M, Pitman H, Rajpoot N et al. (2019), Journal of Pathology: Clinical Research, 5(2), 81-90
Identification of C. elegans strains using a fully convolutional neural network on behavioural dynamics
Javer A, Brown AEX, Kokkinos I & Rittscher J (2019), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11134 LNCS, 455-464
Precision immunoprofiling by image analysis and artificial intelligence
Koelzer VH, Sirinukunwattana K, Rittscher J & Mertz KD (2018), Virchows Archiv, 474(4), 511-522
BibTeX
@article{precisionimmuno-2018/11,
title={Precision immunoprofiling by image analysis and artificial intelligence},
author={Koelzer VH, Sirinukunwattana K, Rittscher J & Mertz KD},
journal={Virchows Archiv},
volume={474},
pages={511-522},
publisher={Springer Berlin Heidelberg},
year = "2018"
}
Improving whole slide segmentation through visual context: a systematic study
Sirinukunwattana K, Khalid Alham N, Verrill C & Rittscher J (2018), MICCAI 2018: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, 11071, 192-200
Pathologist Assessment of Novel Histological Features in Prostate Cancer
Tupper PM, Rao S, Bryant R, Lamb A, Hamdy F et al. (2018), JOURNAL OF PATHOLOGY, 246, S42-S42
BibTeX
@inproceedings{pathologistasse-2018/9,
title={Pathologist Assessment of Novel Histological Features in Prostate Cancer},
author={Tupper PM, Rao S, Bryant R, Lamb A, Hamdy F et al.},
pages={S42-S42},
year = "2018"
}
Global probabilistic models for enhancing segmentation with convolutional networks
Fan M & Rittscher J (2018), IEEE International Symposium on Biomedical Imaging, 2018(1)
Sensorless adaptive optics for isoSTED nanoscopy
Antonello J, Hao X, Allgeyer ES, Bewersdorf J, Rittscher J et al. (2018), Progress in Biomedical Optics and Imaging - Proceedings of SPIE: Adaptive Optics and Wavefront Control for Biological Systems IV, 10502
Discovery of rare phenotypes in cellular images using weakly supervised deep learning
Sailem H, Arias-Garcia M, Bakal C, Zisserman A & Rittscher J (2018), IEEE Conference on Computer Vision Workshops (ICCVW 2017)
Analysis of live cell images: methods, tools and opportunities
Nketia T, Sailem H, Rohde G, Machiraju R & Rittscher J (2017), Methods, 115, 65-79
Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer
Roxanis I, Colling R, Rakha EA, Green A, Rittscher J et al. (2017), LABORATORY INVESTIGATION, 97, 68A-68A
BibTeX
@inproceedings{digitalanalysis-2017/2,
title={Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer},
author={Roxanis I, Colling R, Rakha EA, Green A, Rittscher J et al.},
booktitle={106th Annual Meeting of the United-States-and-Canadian-Academy-of-Pathology (USCAP)},
pages={68A-68A},
year = "2017"
}
Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer
Roxanis I, Colling R, Rakha EA, Green A, Rittscher J et al. (2017), MODERN PATHOLOGY, 30, 68A-68A
BibTeX
@inproceedings{digitalanalysis-2017/2,
title={Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer},
author={Roxanis I, Colling R, Rakha EA, Green A, Rittscher J et al.},
booktitle={106th Annual Meeting of the United-States-and-Canadian-Academy-of-Pathology (USCAP)},
pages={68A-68A},
year = "2017"
}
System and method for multiplexed biomarker quantitation using single cell segmentation on sequentially stained tissue
Santamaria-Pang A, Rittscher J, Padfield D, Can A, Pang Z et al. (2015)
BibTeX
@misc{systemandmethod-2015/3,
title={System and method for multiplexed biomarker quantitation using single cell segmentation on sequentially stained tissue},
author={Santamaria-Pang A, Rittscher J, Padfield D, Can A, Pang Z et al.},
year = "2015"
}
CELL SEGMENTATION AND CLASSIFICATION BY HIERARCHICAL SUPERVISED SHAPE RANKING
Santamaria-Pang A, Rittscher J, Gerdes M, Padfield D & IEEE (2015), 2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 1296-1299
BibTeX
@inproceedings{cellsegmentatio-2015/,
title={CELL SEGMENTATION AND CLASSIFICATION BY HIERARCHICAL SUPERVISED SHAPE RANKING},
author={Santamaria-Pang A, Rittscher J, Gerdes M, Padfield D & IEEE },
pages={1296-1299},
year = "2015"
}
TOWARDS QUANTIFYING THE IMPACT OF CELL BOUNDARY ESTIMATION ON MORPHOMETRIC ANALYSIS FOR PHENOTYPIC SCREENING
Nketia TA, Noble JA, Rittscher J & IEEE (2015), 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 781-784
BibTeX
@inproceedings{towardsquantify-2015/,
title={TOWARDS QUANTIFYING THE IMPACT OF CELL BOUNDARY ESTIMATION ON MORPHOMETRIC ANALYSIS FOR PHENOTYPIC SCREENING},
author={Nketia TA, Noble JA, Rittscher J & IEEE },
pages={781-784},
year = "2015"
}
MAPPING FOR TISSUE BASED CYTOMETRY
Rittscher J, Santamaria-Pang A & IEEE (2014), 2014 IEEE 11TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 278-281
BibTeX
@inproceedings{mappingfortissu-2014/,
title={MAPPING FOR TISSUE BASED CYTOMETRY},
author={Rittscher J, Santamaria-Pang A & IEEE },
pages={278-281},
year = "2014"
}
Cell segmentation and classification via unsupervised shape ranking
Santamaria-Pang A, Huangy Y & Rittscher J (2013), Proceedings - International Symposium on Biomedical Imaging, 406-409
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue
Gerdes MJ, Sevinsky CJ, Sood A, Adak S, Bello MO et al. (2013), Proceedings of the National Academy of Sciences, 110(29), 11982-11987
BibTeX
@article{highlymultiplex-2013/7,
title={Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue},
author={Gerdes MJ, Sevinsky CJ, Sood A, Adak S, Bello MO et al.},
journal={Proceedings of the National Academy of Sciences},
volume={110},
pages={11982-11987},
publisher={Proceedings of the National Academy of Sciences},
year = "2013"
}
Monitoring cardiomyocyte motionin real time through image registration and time series analysis
Liu X, Iyengar SG & Rittscher J (2012), Proceedings - International Symposium on Biomedical Imaging, 1308-1311
Tissue segmentation and classification using graph-based unsupervised clustering
Margolis D, Santamaria-Pang A & Rittscher J (2012), Proceedings - International Symposium on Biomedical Imaging, 162-165
Digitally adjusting chromogenic dye proportions in brightfield microscopy images.
Bilgin CC, Rittscher J, Filkins R & Can A (2012), J Microsc, 245(3), 319-330
Methods and algorithms for extracting high-content signatures from cells, tissues, and model organisms
Rittscher J, Padfield D, Santamaria A, Tu J, Can A et al. (2011), Proceedings - International Symposium on Biomedical Imaging, 1712-1716
BibTeX
@article{methodsandalgor-2011/11,
title={Methods and algorithms for extracting high-content signatures from cells, tissues, and model organisms},
author={Rittscher J, Padfield D, Santamaria A, Tu J, Can A et al.},
journal={Proceedings - International Symposium on Biomedical Imaging},
pages={1712-1716},
year = "2011"
}
Quantitative biological studies enabled by robust cell tracking
Padfield D, Rittscher J & Roysam B (2011), Proceedings - International Symposium on Biomedical Imaging, 1929-1934
Non-parametric population analysis of cellular phenotypes
Singh S, Janoos F, Pécot T, Caserta E, Huang K et al. (2011), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6892 LNCS(PART 2), 343-351
Multi-class object layout with unsupervised image classification and object localization
Lim SN, Doretto G & Rittscher J (2011), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6938 LNCS(PART 1), 573-585
Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis
Padfield D, Rittscher J & Roysam B (2011), Medical Image Analysis, 15(4), 650-668
Identifying nuclear phenotypes using semi-supervised metric learning
Singh S, Janoos F, Pécot T, Caserta E, Leone G et al. (2011), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6801 LNCS, 398-410
LPSM: Fitting shape model by linear programming
Tu J, Laflen B, Liu X, Bello M, Rittscher J et al. (2011), 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011, 252-258
Appearance-based person reidentification in camera networks: Problem overview and current approaches
Doretto G, Sebastian T, Tu P & Rittscher J (2011), Journal of Ambient Intelligence and Humanized Computing, 2(2), 127-151
BibTeX
@article{appearancebased-2011/6,
title={Appearance-based person reidentification in camera networks: Problem overview and current approaches},
author={Doretto G, Sebastian T, Tu P & Rittscher J},
journal={Journal of Ambient Intelligence and Humanized Computing},
volume={2},
pages={127-151},
year = "2011"
}
Non-parametric population analysis of cellular phenotypes.
Singh S, Janoos F, Pécot T, Caserta E, Huang K et al. (2011), Med Image Comput Comput Assist Interv, 14(Pt 2), 343-351
Identifying nuclear phenotypes using semi-supervised metric learning.
Singh S, Janoos F, Pécot T, Caserta E, Leone G et al. (2011), Inf Process Med Imaging, 22, 398-410
Automated training data generation for microscopy focus classification
Gao D, Padfield D, Rittscher J & McKay R (2010), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6362 LNCS(PART 2), 446-453
BibTeX
@article{automatedtraini-2010/11,
title={Automated training data generation for microscopy focus classification},
author={Gao D, Padfield D, Rittscher J & McKay R},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume={6362 LNCS},
pages={446-453},
year = "2010"
}
Characterization of biological processes through automated image analysis.
Rittscher J (2010), Annu Rev Biomed Eng, 12, 315-344
Analysis of spatial variation of nuclear morphology in tissue microenvironments
Singh S, Raman S, Caserta E, Leone G, Ostrowski M et al. (2010), 2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings, 1293-1296
BibTeX
@article{analysisofspati-2010/8,
title={Analysis of spatial variation of nuclear morphology in tissue microenvironments},
author={Singh S, Raman S, Caserta E, Leone G, Ostrowski M et al.},
journal={2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings},
pages={1293-1296},
year = "2010"
}
Automated training data generation for microscopy focus classification.
Gao D, Padfield D, Rittscher J & McKay R (2010), Med Image Comput Comput Assist Interv, 13(Pt 2), 446-453
A model change detection approach to dynamic scene modeling
Kim SJ, Doretto G, Rittscher J, Tu P, Krahnstoever N et al. (2009), 6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009, 490-495
BibTeX
@article{amodelchangedet-2009/12,
title={A model change detection approach to dynamic scene modeling},
author={Kim SJ, Doretto G, Rittscher J, Tu P, Krahnstoever N et al.},
journal={6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009},
pages={490-495},
year = "2009"
}
Coupled minimum-cost flow cell tracking
Padfield D, Rittscher J & Roysam B (2009), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5636 LNCS, 374-385
BibTeX
@article{coupledminimumc-2009/9,
title={Coupled minimum-cost flow cell tracking},
author={Padfield D, Rittscher J & Roysam B},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume={5636 LNCS},
pages={374-385},
year = "2009"
}
Spatio-temporal cell cycle phase analysis using level sets and fast marching methods
Padfield D, Rittscher J, Thomas N & Roysam B (2009), Medical Image Analysis, 13(1), 143-155
Automated System and method for screening zebrafish
Rittscher J, Yekta A, Bello M, Tu J & Seng W (2009)
BibTeX
@misc{automatedsystem-2009/,
title={Automated System and method for screening zebrafish},
author={Rittscher J, Yekta A, Bello M, Tu J & Seng W},
year = "2009"
}
Coupled minimum-cost flow cell tracking.
Padfield D, Rittscher J & Roysam B (2009), Inf Process Med Imaging, 21, 374-385
Methods for monitoring cellular motion and function
Padfield D, Rittscher J & Roysam B (2008), Conference Record - Asilomar Conference on Signals, Systems and Computers, 47-50
Spatio-temporal cell segmentation and tracking for automated screening
Padfield D, Rittscher J & Roysam B (2008), 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI, 376-379
BibTeX
@article{spatiotemporalc-2008/9,
title={Spatio-temporal cell segmentation and tracking for automated screening},
author={Padfield D, Rittscher J & Roysam B},
journal={2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI},
pages={376-379},
year = "2008"
}
Unified crowd segmentation
Tu P, Sebastian T, Doretto G, Krahnstoever N, Rittscher J et al. (2008), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5305 LNCS(PART 4), 691-704
BibTeX
@article{unifiedcrowdseg-2008/1,
title={Unified crowd segmentation},
author={Tu P, Sebastian T, Doretto G, Krahnstoever N, Rittscher J et al.},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume={5305 LNCS},
pages={691-704},
year = "2008"
}
Microscopic Image Analysis for Life Science Applications
Rittscher J, Machiraju R & Wong STC (2008)
BibTeX
@book{microscopicimag-2008/,
title={Microscopic Image Analysis for Life Science Applications},
author={Rittscher J, Machiraju R & Wong STC},
publisher={Artech House Publishers},
year = "2008"
}
View adaptive detection and distributed site wide tracking
Tu P, Krahstoever N & Rittscher J (2007), 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007 Proceedings, 57-62
Shape and appearance context modeling
Wang X, Doretto G, Sebastian T, Rittscher J & Tu P (2007), Proceedings of the IEEE International Conference on Computer Vision
An intelligent video framework for homeland protection
Tu PH, Doretto G, Krahnstoever NO, Perera AGA, Wheeler FW et al. (2007), Proceedings of SPIE - The International Society for Optical Engineering, 6562
Multi-target tracking using hybrid particle filtering
Rittscher J, Krahnstoever N & Galup L (2007), Proceedings - Seventh IEEE Workshop on Applications of Computer Vision, WACV 2005, 447-454
A multi-objective supplier selection model under stochastic demand conditions
Liao Z & Rittscher J (2007), International Journal of Production Economics, 105(1), 150-159
Optimal pose for face recognition
Liu X, Chen T & Rittscher J (2006), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 1439-1446
Person reidentification using spatiotemporal appearance
Gheissari N, Sebastian TB, Tu PH, Rittscher J & Hartley R (2006), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 1528-1535
BibTeX
@article{personreidentif-2006/12,
title={Person reidentification using spatiotemporal appearance},
author={Gheissari N, Sebastian TB, Tu PH, Rittscher J & Hartley R},
journal={Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
volume={2},
pages={1528-1535},
year = "2006"
}
Validation methods for cell cycle analysis algorithms in confocal fluorescence images
Padfield D, Rittscher J, Thomas N & Roysam B (2006), 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006
Computing phagocytosis index for high-throughput applications
Sebastian T, Rittscher J & Yu L (2006), 2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings, 2006, 546-549
BibTeX
@article{computingphagoc-2006/11,
title={Computing phagocytosis index for high-throughput applications},
author={Sebastian T, Rittscher J & Yu L},
journal={2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings},
volume={2006},
pages={546-549},
year = "2006"
}
Spatio-temporal cell cycle analysis using 3D level set segmentation of unstained nuclei in line scan confocal fluorescence images
Padfield DR, Rittscher J, Sebastian T, Thomas N, Roysam B et al. (2006), 2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3, 1036-+
BibTeX
@inproceedings{spatiotemporalc-2006/,
title={Spatio-temporal cell cycle analysis using 3D level set segmentation of unstained nuclei in line scan confocal fluorescence images},
author={Padfield DR, Rittscher J, Sebastian T, Thomas N, Roysam B et al.},
pages={1036-+},
year = "2006"
}
Detecting and counting people in surveillance applications
Liu X, Tu PH, Rittscher J, Perera A & Krahnstoever N (2005), IEEE International Conference on Advanced Video and Signal Based Surveillance - Proceedings of AVSS 2005, 2005, 306-311
BibTeX
@article{detectingandcou-2005/12,
title={Detecting and counting people in surveillance applications},
author={Liu X, Tu PH, Rittscher J, Perera A & Krahnstoever N},
journal={IEEE International Conference on Advanced Video and Signal Based Surveillance - Proceedings of AVSS 2005},
volume={2005},
pages={306-311},
year = "2005"
}
Potential analysis made by oneself
Keller M & Rittscher J (2005), STAHL UND EISEN, 125(6), 22-23
BibTeX
@article{potentialanalys-2005/6,
title={Potential analysis made by oneself},
author={Keller M & Rittscher J},
journal={STAHL UND EISEN},
volume={125},
pages={22-23},
year = "2005"
}
Activity recognition using visual tracking and RFID
Krahnstoever N, Rittscher J, Tu P, Chean K & Tomlinson T (2005), Proceedings - Seventh IEEE Workshop on Applications of Computer Vision, WACV 2005, 494-500
Simultaneous estimation of segmentation and shape
Rittscher J, Tu PH & Krahnstoever N (2005), Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, II, 486-493
BibTeX
@article{simultaneousest-2005/1,
title={Simultaneous estimation of segmentation and shape},
author={Rittscher J, Tu PH & Krahnstoever N},
journal={Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005},
volume={II},
pages={486-493},
year = "2005"
}
Disturbance management in large logistics networks
Hinrichs J, Rittscher J, Laakmann F & Hellingrath B (2005), ICIL 2005: Proceedings of the International Conference on Industrial Logistics, 141-152
BibTeX
@inproceedings{disturbancemana-2005/,
title={Disturbance management in large logistics networks},
author={Hinrichs J, Rittscher J, Laakmann F & Hellingrath B},
pages={141-152},
year = "2005"
}
Collaborative ramp-up planning and controlling
Hinrichs J, Rittscher J, Laakmann F & Hellingrath (2004), 2nd IEEE International Conference on Industrial Informatics, INDIN'04, 180-183
BibTeX
@inproceedings{collaborativera-2004/12,
title={Collaborative ramp-up planning and controlling},
author={Hinrichs J, Rittscher J, Laakmann F & Hellingrath },
pages={180-183},
year = "2004"
}
Crowd segmentation through emergent labeling
Tu PH & Rittscher J (2004), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3247, 187-198
BibTeX
@article{crowdsegmentati-2004/1,
title={Crowd segmentation through emergent labeling},
author={Tu PH & Rittscher J},
journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume={3247},
pages={187-198},
year = "2004"
}
Video content annotation using visual analysis and a large semantic knowledgebase
Hoogs A, Rittscher J, Stein G & Schmiederer J (2003), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2
BibTeX
@article{videocontentann-2003/9,
title={Video content annotation using visual analysis and a large semantic knowledgebase},
author={Hoogs A, Rittscher J, Stein G & Schmiederer J},
journal={Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
volume={2},
year = "2003"
}
Mathematical modelling of animate and intentional motion.
Rittscher J, Blake A, Hoogs A & Stein G (2003), Philos Trans R Soc Lond B Biol Sci, 358(1431), 475-490
Enabling video annotation using a semantic database extended with visual knowledge
Stein GC, Rittscher J, Hoogs A, IEEE , IEEE et al. (2003), 2003 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOL I, PROCEEDINGS, 161-164
BibTeX
@inproceedings{enablingvideoan-2003/,
title={Enabling video annotation using a semantic database extended with visual knowledge},
author={Stein GC, Rittscher J, Hoogs A, IEEE , IEEE et al.},
pages={161-164},
year = "2003"
}
Site calibration for large indoor scenes
Tu P, Rittscher J & Kelliher T (2003), IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, PROCEEDINGS, 358-363
Towards the automatic analysis of complex human body motions
Rittscher J, Blake A & Roberts SJ (2002), IMAGE AND VISION COMPUTING, 20(12), 905-916
An HMM-based segmentation method for traffic monitoring movies
Kato J, Watanabe T, Joga S, Rittscher J & Blake A (2002), IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9), 1291-1296
Guiding random particles by deterministic search
Sullivan J & Rittscher J (2001), Proceedings of the IEEE International Conference on Computer Vision, 1, 323-330
Learning and classification of complex dynamics
North B, Blake A, Isard M & Rittscher J (2000), IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 22(9), 1016-1034
Statistical foreground modelling for object localisation
Sullivan J, Blake A & Rittscher J (2000), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1843, 307-323
A probabilistic background model for tracking
Rittscher J, Kato J, Joga S & Blake A (2000), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1843, 336-350
An integral criterion for detecting boundary edges and textured regions
Rittscher J & Sullivan J (2000), 15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, PROCEEDINGS, 1064-1067
BibTeX
@inproceedings{anintegralcrite-2000/,
title={An integral criterion for detecting boundary edges and textured regions},
author={Rittscher J & Sullivan J},
pages={1064-1067},
year = "2000"
}
Classification of human body motion
Rittscher J & Blake A (1999), Proceedings of the IEEE International Conference on Computer Vision, 1, 634-639
Foreign Object Detection and Quantification of Fat Content Using A Novel Multiplexing Electric Field Sensor
Rittscher AE, Sulaimalebbe A, Capdeboscq Y & Rittscher J (0), N/A (arXiv)
BibTeX
@article{foreignobjectde-/,
title={Foreign Object Detection and Quantification of Fat Content Using A Novel
Multiplexing Electric Field Sensor},
author={Rittscher AE, Sulaimalebbe A, Capdeboscq Y & Rittscher J},
journal={N/A (arXiv)}
}
Visualisation of T cell migration in the spleen reveals a network of perivascular pathways that guide entry into T zones
Arnon TI, Chauveau A, Pirgova G, Cheng H-W, De Martin A et al. (0), Immunity
BibTeX
@article{visualisationof-/,
title={Visualisation of T cell migration in the spleen reveals a network of perivascular pathways that guide entry into T zones},
author={Arnon TI, Chauveau A, Pirgova G, Cheng H-W, De Martin A et al.},
journal={Immunity},
publisher={Elsevier}
}
Microscopic fine-grained instance classification through deep attention
Fan M, Chakrabort T, Chang EI-C, Xu Y & Rittscher J (0)
BibTeX
@misc{microscopicfine-/,
title={Microscopic fine-grained instance classification through deep attention},
author={Fan M, Chakrabort T, Chang EI-C, Xu Y & Rittscher J}
}
Automated quality assessment of large digitised histology cohorts by artificial intelligence
Haghighat M, Browning L, Sirinukunwattana K, Malacrino S, Khalid Alham N et al. (0), Scientific Reports
BibTeX
@article{automatedqualit-/,
title={Automated quality assessment of large digitised histology cohorts by artificial intelligence},
author={Haghighat M, Browning L, Sirinukunwattana K, Malacrino S, Khalid Alham N et al.},
journal={Scientific Reports},
publisher={Springer Nature}
}
Enhancing Local Context of Histology Features in Vision Transformers
Wood R, Sirinukunwattana K, Domingo E, Sauer A, Lafarge M et al. (0)
BibTeX
@inproceedings{enhancinglocalc-/,
title={Enhancing Local Context of Histology Features in Vision Transformers},
author={Wood R, Sirinukunwattana K, Domingo E, Sauer A, Lafarge M et al.},
booktitle={MICCAI 2022}
}
Continuous Indexing of Fibrosis (CIF): Improving the Assessment and Classification of MPN Patients
Ryou H, Sirinukunwattana K, Aberdeen A, Grindstaff G, Stolz B et al. (0)