Professor
Jens Rittscher
Professor of Engineering Science
Professorial Research Fellow
Fellow of Harris Manchester College
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All publications by Professor Rittscher
CtrlEndoDiff: Diffusion-Based Synthetic Image Generation for Enhanced ACF Segmentation
Albokhari R,  Debnath B,  Henry D,  Johnson M,  Bailey A,  East JE,  Rittscher J,  et al. (2026)
Unsupervised Discovery of Spatiotypes and Context-Aware Graph Neural Networks for Modeling Clinical Endpoints
Dawood M,  Thomas E,  Cooper R,  Pescia C,  Sozanska A,  Ryou H,  Royston D,  Rittscher J,  et al. (2026)
Chemo-prAIdict Breast: A deep learning solution for predicting residual disease on biopsies of breast cancer patients treated with neoadjuvant chemotherapy
Valderrama NF,  Morel L-O,  Mweze DT,  Derangère V,  Desmoulins I,  Mayeur D,  Kaderbhai C,  Ilie S,  Hennequin A,  Roussot N,  Bergeron A,  Beltjens F,  Pescia C,  Morel H-P,  Coutant C,  Rittscher J,  Arnould L,  Vinçon N,  Ladoire S,  et al. (2026)
Harness Behavioural Analysis for Unpacking the Bio-Interpretability of Pathology Foundation Models
Hu Y,  Batchkala G,  Gaitskell K,  Domingo E,  Li B,  Zhang T,  Li Z,  Friedrich M,  Woodcock D,  Verrill C,  Rittscher J,  et al. (2026)
Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priors
Xu Z,  Li B,  Hu Y,  Zhang C,  East J,  Ali S,  Rittscher J,  et al. (2026)
Accuracy of Diagnosis in Myeloproliferative Neoplasms With Splanchnic Vein Thrombosis (MPN‐SVT)
Sreedhar BR,  Ryou H,  O'Riordan A,  Hargreaves R,  Chauhan N,  Alexe D,  Alimam S,  Rittscher J,  Pomplun S,  Royston D,  Sekhar M,  et al. (2026)
Patchsurg: Leveraging Synthetic Datasets for High-Fidelity Depth Estimation in Surgery
Xu Z,  Zhang C,  Rittscher J,  Ali S,  et al. (2026)
Decoding fibrosis: transcriptomic and clinical insights via AI-derived collagen deposition phenotypes in MASLD
Wojciechowska M,  Thing M,  Hu Y,  Mazzoni G,  Harder LM,  Werge MP,  Kimer N,  Das V,  Martinez JM,  Prada-Medina C,  Vyberg M,  Goldin R,  Serizawa R,  Tomlinson J,  Bartholdy A,  Jensen M,  Galsgaard ED,  Woodcock DJ,  Hvid H,  Pfister DR,  Jurtz VI,  Gluud LL,  Rittscher J,  et al. (2026)
Image-based consensus molecular subtypes and colon cancer recurrence: Understanding the impact of lifestyle factors across subtypes of colon cancer
Wesselink E,  Kok DE,  Lafarge MW,  van Lanen AS,  Nagtegaal ID,  Sulter M,  Koopman M,  de Wilt JHW,  Kampman E,  Kölzer VH,  May AM,  van Duijnhoven FJB,  Sirinukunwattana K,  Domingo E,  Maughan T,  Rittscher J,  et al. (2026)
Epigenetic modulation of stromal cell states underpins pathological tissue niches in Crohn’s disease
Koplev S,  Sharma O,  Woelfel S,  Huang N,  Pohin M,  Feile A,  Warschinke M,  Artero MR,  Suthakaran S,  Sarropoulos I,  Pett JP,  Nyman J,  Thomas T,  Pham D,  Li B,  Attar M,  Pakpoor J,  Milosevic-Hutton K,  Easton A,  Butler M,  Dunford J,  Philpott M,  Coles M,  Buckley CD,  Dendrou C,  Shamiyah K,  Kretschmer L,  Dratva L,  Issa F,  Hester J,  Rittscher J,  Walsh A,  Travis SP,  Progatzky F,  Unger LW,  Bignell M,  Baker K,  George B,  Al-Mossawi H,  Klenerman P,  Mosig AS,  Oppermann U,  Teichmann SA,  Powrie FM,  Friedrich M,  et al. (2026)
Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images
Wood R,  Domingo E,  Koelzer VH,  Maughan TS,  Rittscher J,  et al. (2025)
Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysis.
Schoenpflug LA,  Chatzipli A,  Sirinukunwattana K,  Richman S,  Blake A,  Robineau J,  Mertz KD,  Verrill C,  Leedham SJ,  Hardy C,  Whalley C,  Redmond K,  Dunne P,  Walker S,  Beggs AD,  McDermott U,  Murray GI,  Samuel LM,  Seymour M,  Tomlinson I,  Quirke P,  S:CORT consortium ,  Rittscher J,  Maughan T,  Domingo E,  Koelzer VH,  et al. (2025)
8 Novel enhancement of multimodality treatment of prostate cancer, combining radiotherapy,vascular-targeted photodynamic therapy, and immunotherapy
Sjoberg HT,  Macklin S,  Philippou Y,  Murphy EA,  Tullis IDC,  Jones KI,  Stribbling SM,  Parkes EE,  Edmondson EF,  Scheiblin DA,  Lockett SJ,  Wink DA,  Rittscher J,  Preise D,  Agemy L,  Yechezkel T,  Giaccia A,  Mills IG,  Muschel RJ,  Scherz AVB,  Hamdy FC,  Bryant RJ,  et al. (2025)
8 Novel enhancement of multimodality treatment of prostate cancer, combining radiotherapy,vascular-targeted photodynamic therapy, and immunotherapy
Sjoberg HT,  Macklin S,  Philippou Y,  Murphy EA,  Tullis IDC,  Jones KI,  Stribbling SM,  Parkes EE,  Edmondson EF,  Scheiblin DA,  Lockett SJ,  Wink DA,  Rittscher J,  Preise D,  Agemy L,  Yechezkel T,  Giaccia A,  Mills IG,  Muschel RJ,  Scherz AVB,  Hamdy FC,  Bryant RJ,  et al. (2025)
Reticulin-Free Quantitation of Bone Marrow Fibrosis in MPNs: Utility and Applications.
Ryou H,  Thomas E,  Wojciechowska M,  Harding L,  Tam KH,  Wang R,  Hu X,  Rittscher J,  Cooper R,  Royston D,  et al. (2025)
MSP-tracker: A versatile vesicle tracking software tool used to reveal the spatial control of polarized secretion in Drosophila epithelial cells.
Richens JH,  Dmitrieva M,  Zenner HL,  Muschalik N,  Butler R,  Glashauser J,  Camelo C,  Luschnig S,  Munro S,  Rittscher J,  St Johnston D,  et al. (2025)
Delineating Mpl-dependent and -independent phenotypes of Jak2 V617F- positive MPNs in vivo.
Papadopoulos N,  Nédélec A,  Rahmani Y,  Ryou H,  Defour J-P,  Rittscher J,  Royston D,  Constantinescu SN,  et al. (2025)
Decoding fibrosis: transcriptomic and clinical insights via AI-derived collagen clusters in MASLD
Wojciechowska M,  Thing M,  Hu Y,  Mazzoni G,  Harder LM,  Werge M,  Das V,  Vyberg M,  Goldin RD,  Serizawa R,  Galsgaard E,  Woodcock D,  Hvid H,  Pfister D,  Jurtz V,  Gluud LL,  Rittscher J,  et al. (2025)
Synergies between Clinicians, Academia and Industry in the Age of AI
Byrne MF,  Rittscher J,  East JE,  et al. (2025)
Decoding Fibrosis: Transcriptomic and Clinical Insights via AI-Derived Collagen Deposition Phenotypes in MASLD
Wojciechowska M,  Thing M,  Hu Y,  Mazzoni G,  Harder LM,  Werge MP,  Kimer N,  Das V,  Martinez JM,  Prada-Medina C,  Vyberg M,  Goldin R,  Serizawa R,  Tomlinson J,  Galsgaard ED,  Woodcock DJ,  Hvid H,  Pfister DR,  Jurtz VI,  Gluud LL,  Rittscher J,  et al. (2025)
EXABS-184-MPN: Refining Diagnosis, Prognosis, and Management of MPNs With AI/ML
Cooper R,  Thomas E,  Hu X,  Muhammad D,  Ryou H,  Sirinukunwattana K,  Aberdeen A,  Ruane S,  Ebsworth T,  Sozanska A,  Pescia C,  Rittscher J,  Daniel Royston M,  et al. (2025)
Decoding Fibrosis: Transcriptomic and Clinical Insights via AI-Derived Collagen Deposition Phenotypes in MASLD
Wojciechowska M,  Thing M,  Hu Y,  Mazzoni G,  Harder LM,  Werge MP,  Kimer N,  Das V,  Martinez JM,  Prada-Medina C,  Vyberg M,  Goldin R,  Serizawa R,  Tomlinson J,  Galsgaard ED,  Woodcock DJ,  Hvid H,  Pfister DR,  Jurtz VI,  Gluud LL,  Rittscher J,  et al. (2025)
Histology-informed tiling of whole tissue sections improves the interpretability and predictability of cancer relapse and genetic alterations
Bonnaffé W,  Hu Y,  Chatrian A,  Fan M,  Malacrino S,  Figiel S,  Group CIP,  Rao SR,  Colling R,  Bryant RJ,  Hamdy FC,  Woodcock DJ,  Mills IG,  Verrill C,  Rittscher J,  et al. (2025)
Toward precision pathology: Deep learning supported fibrosis grading augments performance of international hematopathologists in a large real-world cohort
Ebsworth T,  Ruane S,  Bhardwaj N,  Cooper R,  Green A,  Hay D,  Ihlow J,  Jelloul F,  Kanagal-Shamanna R,  Macklin P,  Manohar V,  Olmeda E,  Ong M,  Pescia C,  Quesada A,  Bashir S,  Maxwell S,  Sirinukunwattana K,  Aberdeen A,  Rittscher J,  Royston D,  et al. (2025)
Redefining the topology of the human bone marrow using augmented spatial transcriptomic analysis
Cooper RA,  Thomas E,  Dawood M,  Ryou H,  Sozanska A,  Pescia C,  McCallion O,  Gupta M,  Teague R,  Hester J,  Issa F,  Woodcock DJ,  Psaila B,  Mead A,  Rittscher J,  Royston D,  et al. (2025)
GenST: A Generative Cross-Modal Model for Predicting Spatial Transcriptomics from Histology Images
Wood R,  Hu Y,  Rittscher J,  Li B,  et al. (2025)
Quantitative Analysis of Bone Marrow Features Highlights Heterogeneity in Myelofibrosis Patients Treated with Zinpentraxin Alfa in a Phase II Clinical Study
Ryou H,  Sirinukunwattana K,  Wood R,  Aberdeen A,  Rittscher J,  Weinberg O,  Hasserjian R,  Pozdnyakova O,  Peale F,  Higgins B,  Lundberg P,  Trunzer K,  Harrison CN,  Royston D,  et al. (2024)
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,  Yang C,  Li W,  Galdran A,  Ballester M-ÁG,  Thambawita V,  Hicks S,  Poudel S,  Lee S-W,  Jin Z,  Gan T,  Yu C,  Yan J,  Yeo D,  Lee H,  Tomar NK,  Haithami M,  Ahmed A,  Riegler MA,  Daul C,  Halvorsen P,  et al. (2024)
Annotation-free learning of a spatio-temporal manifold of the cell life cycle.
Delas Peñas K,  Dmitrieva M,  Waithe D,  Rittscher J,  et al. (2024)
Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy
Lafarge MW,  Domingo E,  Sirinukunwattana K,  Wood R,  Samuel L,  Murray G,  Richman SD,  Blake A,  Sebag-Montefiore D,  Gollins S,  Klieser E,  Neureiter D,  Huemer F,  Greil R,  Dunne P,  Quirke P,  Weiss L,  Rittscher J,  Maughan T,  Koelzer VH,  et al. (2024)
Accurate subtyping of lung cancers by modelling class dependencies
Batchkala G,  Li B,  Fan M,  McCole M,  Brambilla C,  Gleeson F,  Rittscher J,  et al. (2024)
38 Modelling Class Dependencies for Lung Cancer Subtyping from Digitised Pathology Images
Batchkala G,  Fan M,  Li B,  McCole M,  Brambilla C,  Gleeson F,  Rittscher J,  et al. (2024)
Artificial Intelligence-Based Quality Assessment of Histopathology Whole-Slide Images within a Clinical Workflow: Assessment of 'PathProfiler' in a Diagnostic Pathology Setting.
Browning L,  Jesus C,  Malacrino S,  Guan Y,  White K,  Puddle A,  Alham NK,  Haghighat M,  Colling R,  Birks J,  Rittscher J,  Verrill C,  et al. (2024)
Quantitative analysis of bone marrow fibrosis highlights heterogeneity in myelofibrosis and augments histological assessment: An Insight from a phase II clinical study of zinpentraxin alfa.
Ryou H,  Sirinukunwattana K,  Wood R,  Aberdeen A,  Rittscher J,  Weinberg OK,  Hasserjian R,  Pozdnyakova O,  Peale F,  Higgins B,  Lundberg P,  Trunzer K,  Harrison CN,  Royston D,  et al. (2024)
Adjuvant COX inhibition augments STING signaling and cytolytic T cell infiltration in irradiated 4T1 tumors.
Ridnour LA,  Cheng RY,  Kedei N,  Somasundaram V,  Bhattacharyya DD,  Basudhar D,  Wink AL,  Walke AJ,  Kim C,  Heinz WF,  Edmondson EF,  Butcher DO,  Warner AC,  Dorsey TH,  Pore M,  Kinders RJ,  Lipkowitz S,  Bryant RJ,  Rittscher J,  Wong ST,  Hewitt SM,  Chang JC,  Shalaby A,  Callagy GM,  Glynn SA,  Ambs S,  Anderson SK,  McVicar DW,  Lockett SJ,  Wink DA,  et al. (2024)
Characterising borderline areas in bladder tumour grading with Bayesian graph neural networks
Gao S,  Browning L,  Alham NK,  Protheroe A,  Edwards K,  Hamblin J,  Rittscher J,  Verrill C,  et al. (2024)
Tumor NOS2 and COX2 Spatial Juxtaposition with CD8+ T Cells Promote Metastatic and Cancer Stem Cell Niches that Lead to Poor Outcome in ER- Breast Cancer.
Ridnour LA,  Heinz WF,  Cheng RY,  Wink AL,  Kedei N,  Pore M,  Imtiaz F,  Femino EL,  Gonzalez AL,  Coutinho LL,  Moffat RL,  Butcher D,  Edmondson EF,  Li X,  Rangel MC,  Kinders RJ,  Rittscher J,  Lipkowitz S,  Wong STC,  Anderson SK,  McVicar DW,  Glynn SA,  Billiar TR,  Chang JC,  Hewitt SM,  Ambs S,  Lockett SJ,  Wink DA,  et al. (2024)
MultiVarNet - Predicting Tumour Mutational Status at the Protein Level
Morel L-O,  Muzammel M,  Vinçon N,  Derangère V,  Ladoire S,  Rittscher J,  et al. (2024)
Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders.
Sauer A,  Tian Y,  Bewersdorf J,  Rittscher J,  et al. (2024)
Editorial for Special Issue on Foundation Models for Medical Image Analysis.
Wang X,  Wang D,  Li X,  Rittscher J,  Metaxas D,  Zhang S,  et al. (2024)
Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Generative Latent Priors
Xu Z,  Li B,  Hu Y,  Zhang C,  East J,  Ali S,  Rittscher J,  et al. (2024)
Mapping the Human Bone Marrow in Myeloproliferative Neoplasia Using Spatial Transcriptomics
Cooper R,  Thomas E,  Muhammad D,  Pescia C,  Sozanska A,  McCallion O,  Ryou H,  Teague R,  Liu AKL,  Hester J,  Issa F,  Psaila B,  Mead AJ,  Rittscher J,  Woodcock D,  Royston D,  et al. (2024)
Correction: Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Harrington HA,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2023)
Correction: Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Harrington HA,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2023)
Correction: Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Harrington HA,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2023)
A multi-centre polyp detection and segmentation dataset for generalisability assessment
Ali S,  Jha D,  Ghatwary N,  Realdon S,  Cannizzaro R,  Salem OE,  Lamarque D,  Daul C,  Riegler MA,  Anonsen KV,  Petlund A,  Halvorsen P,  Rittscher J,  de Lange T,  East JE,  et al. (2023)
Beyond attention: deriving biologically interpretable insights from weakly-supervised multiple-instance learning models
Bonnaffé W,  Group CIP,  Hamdy F,  Hu Y,  Mills I,  Rittscher J,  Verrill C,  Woodcock DJ,  et al. (2023)
Quantitative interpretation of bone marrow biopsies in MPN—what's the point in a molecular age?
Ryou H,  Lomas O,  Theissen H,  Thomas E,  Rittscher J,  Royston D,  et al. (2023)
Deep Visualisation-Based Interpretable Analysis of Digital Pathology Images for Colorectal Cancer
Guérin A,  Basu S,  Chakraborti T,  Rittscher J,  et al. (2023)
Leveraging Inter-Annotator Disagreement for Semi-Supervised Segmentation
Sauer A,  Dmitrieva M,  Han H,  Rittscher J,  et al. (2023)
Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies
Wood R,  Domingo E,  Sirinukunwattana K,  Lafarge MW,  Koelzer VH,  Maughan TS,  Rittscher J,  et al. (2023)
Predicting clinical endpoints and visual changes with quality-weighted tissue-based renal histological features
Tam KH,  Soares MF,  Kers J,  Sharples EJ,  Ploeg RJ,  Kaisar M,  Rittscher J,  et al. (2023)
Evaluating histopathology foundation models for few-shot tissue clustering: an application to LC25000 augmented dataset cleaning
Batchkala G,  Li B,  Rittscher J,  et al. (2023)
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples
Martin NG,  Malacrino S,  Wojciechowska M,  Campo L,  Jones H,  Wedge DC,  Holmes C,  Sirinukunwattana K,  Sailem H,  Verrill C,  Rittscher J,  et al. (2022)
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,  Yang C,  Li W,  Galdran A,  Ballester M-ÁG,  Thambawita V,  Hicks S,  Poudel S,  Lee S-W,  Jin Z,  Gan T,  Yu C,  Yan J,  Yeo D,  Lee H,  Tomar NK,  Haithmi M,  Ahmed A,  Riegler MA,  Daul C,  Halvorsen P,  et al. (2022)
Automated quality assessment of large digitised histology cohorts by artificial intelligence
Haghighat M,  Browning L,  Sirinukunwattana K,  Malacrino S,  Khalid Alham N,  Colling R,  Cui Y,  Rakha E,  Hamdy FC,  Verrill C,  Rittscher J,  et al. (2022)
FANet: a feedback attention network for improved biomedical image segmentation
Tomar NK,  Jha D,  Riegler MA,  Johansen HD,  Johansen D,  Rittscher J,  Halvorsen P,  Ali S,  et al. (2022)
ADDITIVE ANGULAR MARGIN LOSS AND MODEL SCALING NETWORK FOR OPTIMISED COLITIS SCORING
Xu Z,  Ali S,  East J,  Rittscher J,  et al. (2022)
Continuous Indexing of Fibrosis (CIF): Improving the Assessment and Classification of MPN Patients
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz B,  Byrne H,  Harrington H,  Sousos N,  Godfrey A,  Harrison C,  Psaila B,  Mead A,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2022)
Patch-level instance-group discrimination with pretext-invariant learning for colitis scoring
Xu Z,  Ali S,  Gupta S,  Leedham S,  East JE,  Rittscher J,  et al. (2022)
Enhancing local context of histology features in vision transformers
Wood R,  Sirinukunwattana K,  Domingo E,  Sauer A,  Lafarge M,  Koelzer V,  Maughan T,  Rittscher J,  et al. (2022)
RFID analysis of the complexity of cellular pathology workflow—An opportunity for digital pathology
Browning L,  White K,  Siiankoski D,  Colling R,  Roskell D,  Fryer E,  Hemsworth H,  Roberts-Gant S,  Roelofsen R,  Rittscher J,  Verrill C,  et al. (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,  Colling R,  Fryer E,  Rittscher J,  Verrill C,  et al. (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,  Kaisar M,  Rittscher J,  et al. (2022)
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy
Gupta S,  Ali S,  Goldsmith L,  Turney B,  Rittscher J,  et al. (2022)
A graph based neural network approach to immune profiling of multiplexed tissue samples
Martin NG,  Malacrino S,  Wojciechowska M,  Campo L,  Jones H,  Wedge DC,  Holmes C,  Sirinukunwattana K,  Sailem H,  Verrill C,  Rittscher J,  et al. (2022)
Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy
Han H,  Dmitrieva M,  Sauer A,  Tam KH,  Rittscher J,  et al. (2022)
Multi-scale graphical representation of cell environment
Theissen H,  Chakraborty T,  Malacrino S,  Royston D,  Rittscher J,  et al. (2022)
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning
Hu Y,  Sirinukunwattana K,  Gaitskell K,  Wood R,  Verrill C,  Rittscher J,  et al. (2022)
Profiling DNA Damage in 3D Histology Samples
Penas KED,  Haeusler R,  Feng S,  Magidson V,  Dmitrieva M,  Wink D,  Lockett S,  Kinders R,  Rittscher J,  et al. (2022)
Self-supervised Approach for a Fully Assistive Esophageal Surveillance: Quality, Anatomy and Neoplasia Guidance
Xu Z,  Ali S,  Celik N,  Bailey A,  Braden B,  Rittscher J,  et al. (2022)
Active Data Enrichment by Learning What to Annotate in Digital Pathology
Batchkala G,  Chakraborti T,  McCole M,  Gleeson F,  Rittscher J,  et al. (2022)
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Harrington HA,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2022)
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Harrington HA,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2022)
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients
Harrington H,  Ryou H,  Sirinukunwattana K,  Aberdeen A,  Grindstaff G,  Stolz BJ,  Byrne H,  Sousos N,  Godfrey AL,  Harrison CN,  Psaila B,  Mead AJ,  Rees G,  Turner GDH,  Rittscher J,  Royston D,  et al. (2022)
Patch-Level Instance-Group Discrimination with Pretext-Invariant Learning for Colitis Scoring
Xu Z,  Ali S,  Gupta S,  Leedham S,  East JE,  Rittscher J,  et al. (2022)
UNet-eVAE: Iterative Refinement Using VAE Embodied Learning for Endoscopic Image Segmentation
Gupta S,  Ali S,  Xu Z,  Bhattarai B,  Turney B,  Rittscher J,  et al. (2022)
Improving Pathological Distribution Measurements with Bayesian Uncertainty
Tam KH,  Sirinukunwattana K,  Soares MF,  Kaisar M,  Ploeg R,  Rittscher J,  et al. (2021)
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.
Ali S,  Dmitrieva M,  Ghatwary N,  Bano S,  Polat G,  Temizel A,  Krenzer A,  Hekalo A,  Guo YB,  Matuszewski B,  Gridach M,  Voiculescu I,  Yoganand V,  Chavan A,  Raj A,  Nguyen NT,  Tran DQ,  Huynh LD,  Boutry N,  Rezvy S,  Chen H,  Choi YH,  Subramanian A,  Balasubramanian V,  Gao XW,  et al. (2021)
Real-time polyp detection, localization and segmentation in colonoscopy using deep learning
Jha D,  Ali S,  Tomar NK,  Johansen HD,  Johansen D,  Rittscher J,  Riegler MA,  Halvorsen P,  et al. (2021)
The potential of artificial intelligence to detect lymphovascular invasion in testicular cancer
Ghosh A,  Sirinukunwattana K,  Khalid Alham N,  Browning L,  Colling R,  Protheroe A,  Protheroe E,  Jones S,  Aberdeen A,  Rittscher J,  Verrill C,  et al. (2021)
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy
Gupta S,  Ali S,  Goldsmith L,  Turney B,  Rittscher J,  et al. (2021)
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
Tomar NK,  Jha D,  Riegler MA,  Johansen HD,  Johansen D,  Rittscher J,  Halvorsen P,  Ali S,  et al. (2021)
Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies
Colling R,  Browning L,  Alham NK,  Sirinukunwattana K,  Malacrino S,  Haghighat M,  Monks A,  Rittscher J,  Verrill C,  et al. (2021)
Tumour irradiation combined with vascular-targeted photodynamic therapy enhances anti-tumour effects in preclinical prostate cancer
Sjoberg H,  Philippou Y,  Magnussen A,  Tullis I,  Bridges E,  Chatrian A,  Lefebvre J,  Tam K,  Murphy E,  Rittscher J,  Preise D,  Agemy L,  Yechezkel T,  Smart S,  Kinchesh P,  Gilchrist S,  Allen P,  Scheiblin D,  Lockett S,  Wink D,  Lamb A,  Mills I,  Harris A,  Muschel R,  Vojnovic B,  et al. (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,  Lu X,  East JE,  Rittscher J,  Braden B,  et al. (2021)
A multi-centre polyp detection and segmentation dataset for generalisability assessment
Ali S,  Jha D,  Ghatwary N,  Realdon S,  Cannizzaro R,  Salem OE,  Lamarque D,  Daul C,  Riegler MA,  Anonsen KV,  Petlund A,  Halvorsen P,  Rittscher J,  Lange TD,  East JE,  et al. (2021)
Transcriptome and genome evolution during HER2-amplified breast neoplasia
Lu P,  Foley J,  Zhu C,  McNamara K,  Sirinukunwattana K,  Vennam S,  Varma S,  Fehri H,  Srivastava A,  Zhu S,  Rittscher J,  Mallick P,  Curtis C,  West R,  et al. (2021)
EndoUDA: a modality independent segmentation approach for endoscopy imaging
Celik N,  Ali S,  Gupta S,  Braden B,  Rittscher J,  et al. (2021)
Improved Artifact Detection in Endoscopy Imaging Through Profile Pruning
Xu Z,  Ali S,  Gupta S,  Celik N,  Rittscher J,  et al. (2021)
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,  Rittscher J,  et al. (2021)
Contrastive Representations for Continual Learning of Fine-Grained Histology Images
Chakraborti T,  Gleeson F,  Rittscher J,  et al. (2021)
Digital pathology transformation in a supraregional germ cell tumour network
Colling R,  Protheroe A,  Sullivan M,  Macpherson R,  Tuthill M,  Redgwell J,  Traill Z,  Molyneux A,  Johnson E,  Abdullah N,  Taibi A,  Mercer N,  Haynes HR,  Sackville A,  Craft J,  Reis J,  Rees G,  Soares M,  Roberts ISD,  Siiankoski D,  Hemsworth H,  Roskell D,  Roberts-Gant S,  White K,  Rittscher J,  et al. (2021)
Learning Cellular Phenotypes through Supervision.
Theissen H,  Chakraborti T,  Malacrino S,  Sirinukunwattana K,  Royston D,  Rittscher J,  et al. (2021)
Automated annotator: capturing expert knowledge for free
Elmes S,  Chakraborti T,  Fan M,  Uhlig H,  Rittscher J,  et al. (2021)
TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data.
Reina F,  Wigg JMA,  Dmitrieva M,  Vogler B,  Lefebvre J,  Rittscher J,  Eggeling C,  et al. (2021)
Phenotyping of Klf14 mouse white adipose tissue enabled by whole slide segmentation with deep neural networks
Casero R,  Westerberg H,  Horner N,  Yon M,  Aberdeen A,  Grau V,  Cox R,  Rittscher J,  Mallon A-M,  et al. (2021)
Enhancing Local Context of Histology Features in Vision Transformers
Wood R,  Sirinukunwattana K,  Domingo E,  Sauer A,  Lafarge MW,  Koelzer VH,  Maughan TS,  Rittscher J,  et al. (2021)
Identification of C. elegans strains using a fully convolutional neural network on behavioural dynamics
Javer A,  Brown AEX,  Kokkinos I,  Rittscher J,  et al. (2020)
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Ali S,  Zhou F,  Braden B,  Bailey A,  Yang S,  Cheng G,  Zhang P,  Li X,  Kayser M,  Soberanis-Mukul RD,  Albarqouni S,  Wang X,  Wang C,  Watanabe S,  Oksuz I,  Ning Q,  Yang S,  Khan MA,  Gao XW,  Realdon S,  Loshchenov M,  Schnabel JA,  East JE,  Wagnieres G,  Loschenov VB,  et al. (2020)
Endoscopy disease detection challenge 2020
Ali S,  Ghatwary N,  Braden B,  Lamarque D,  Bailey A,  Realdon S,  Cannizzaro R,  Rittscher J,  Daul C,  East J,  et al. (2020)
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,  Zhou FY,  Rittscher J,  Ludewig B,  et al. (2020)
Additive angular margin for few shot learning to classify clinical endoscopy images
Ali S,  Bhattarai B,  Kim T-K,  Rittscher J,  et al. (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,  Cerundolo L,  Bowes E,  Jones S,  Browne M,  Mills I,  Lamb A,  Tomlinson I,  Wedge D,  Browning L,  Sirinukunwattana K,  Palles C,  Hamdy FC,  Rittscher J,  Verrill C,  et al. (2020)
Multi-scale sensorless adaptive optics: application to stimulated emission depletion microscopy
Antonello J,  Barbotin A,  Chong EZ,  Rittscher J,  Booth M,  et al. (2020)
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,  et al. (2020)
Motion induced segmentation of stone fragments in ureteroscopy video
Gupta S,  Ali S,  Goldsmith L,  Turney B,  Rittscher J,  et al. (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,  Leedham S,  Wu C-H,  Maughan T,  Rittscher J,  Koelzer V,  et al. (2020)
Short trajectory segmentation with 1D UNET Framework: application to secretory vesicle dynamics
Dmitrieva M,  Lefebvre J,  delas Peñas K,  Zenner H,  Richens J,  St Johnston D,  Rittscher J,  et al. (2020)
Single-molecule localization microscopy reconstruction using Noise2Noise for super-resolution imaging of actin filaments
Lefebvre J,  Javer Godinez A,  Dmitrieva M,  Rittscher J,  Lewkow B,  Allgeyer E,  Sirinakis G,  Johnston D,  et al. (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,  Booth M,  St Johnston D,  Rittscher J,  et al. (2020)
Fine-grained multi-instance classification in microscopy through deep attention
Fan M,  Chakraborti T,  Chang E,  Xu Y,  Rittscher J,  et al. (2020)
MI-UNet: improved segmentation in ureteroscopy
Gupta S,  Ali S,  Goldsmith L,  Turney B,  Rittscher J,  et al. (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,  Rittscher J,  Verrill C,  et al. (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,  James JA,  Salto-Tellez M,  Snead DRJ,  Verrill C,  et al. (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,  Mead AJ,  Turner G,  Rees G,  Rittscher J,  Royston D,  et al. (2020)
DeepSplit: Segmentation of Microscopy Images Using Multi-task Convolutional Networks
Torr A,  Basaran D,  Sero J,  Rittscher J,  Sailem H,  et al. (2020)
DeepScratch: single-cell based topological metrics of scratch wound assays
Javer Godinez A,  Rittscher J,  Sailem H,  et al. (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,  Cerundolo L,  Bowes E,  Jones S,  Browne M,  Mills I,  Lamb A,  Tomlinson I,  Wedge D,  Browning L,  Sirinukunwattana K,  Palles C,  Hamdy FC,  Rittscher J,  Verrill C,  et al. (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,  Investigators T,  Lu X,  Rittscher J,  Braden B,  et al. (2020)
Microscopic fine-grained instance classification through deep attention
Fan M,  Chakrabort T,  Chang EI-C,  Xu Y,  Rittscher J,  et al. (2020)
A translational pathway of deep learning methods in GastroIntestinal Endoscopy
ALI S,  RITTSCHER J,  et al. (2020)
Unsupervised Adversarial Domain Adaptation For Barrett's Segmentation
Celik N,  Gupta S,  Ali S,  Rittscher J,  et al. (2020)
Supporting dataset for multi-scale sensorless adaptive optics: application to stimulated emission depletion microscopy
Antonello J,  Barbotin A,  Chong EZ,  Rittscher J,  Booth MJ,  et al. (2020)
Precision immunoprofiling by image analysis and artificial intelligence
Koelzer VH,  Sirinukunwattana K,  Rittscher J,  Mertz KD,  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,  Lu X,  et al. (2019)
The use of digital pathology and image analysis in clinical trials
Pell R,  Oien K,  Robinson M,  Pitman H,  Rajpoot N,  Rittscher J,  Snead D,  Verrill C,  et al. (2019)
A deep learning framework for quality assessment and restoration in video endoscopy
Ali S,  Zhou F,  Bailey A,  Braden B,  East J,  Lu X,  Rittscher J,  et al. (2019)
Endoscopy artifact detection (EAD 2019) challenge dataset
Ali S,  Zhou F,  Daul C,  Braden B,  Bailey A,  Realdon S,  East J,  Wagnières G,  Loschenov V,  Grisan E,  Blondel W,  Rittscher J,  et al. (2019)
Improving the diagnosis and classification of Ph-negative myeloproliferative neoplasms through deep phenotyping
Sirinukunwattana K,  Aberdeen A,  Theissen H,  Sousos N,  Psaila B,  Mead AJ,  Turner GDH,  Rees G,  Rittscher J,  Royston D,  et al. (2019)
Capturing variations in nuclear phenotypes
Raman S,  Singh S,  Pecot T,  Caserta E,  Huang K,  Rittscher J,  Leone G,  Machiraju R,  et al. (2019)
Towards the identification of histology based subtypes in prostate cancer
Chatrian A,  Sirinukunwattana K,  Verrill C,  Rittscher J,  et al. (2019)
Moving to a Digital Pathology Supraregional Germ Cell Tumour Service
Colling RT,  White K,  Rittscher J,  Roskell D,  Hemsworth H,  Soares M,  Roberts ISD,  Royston D,  Rees G,  Turner G,  Fryer E,  Roberts-Gant S,  Siiankoski D,  Bryant R,  Molyneux A,  Taibi A,  Johnson E,  Protheroe A,  Tuthill M,  Sullivan M,  Browning L,  Verrill C,  et al. (2019)
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,  Verrill C,  et al. (2019)
Protein tracking by CNN-based candidate pruning and two-step linking with Bayesian network
Dmitrieva M,  Zenner HL,  Richens J,  Johnston DS,  Rittscher J,  et al. (2019)
Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning
Sirinukunwattana K,  Domingo E,  Richman S,  Redmond K,  Blake A,  Verrill C,  Leedham S,  Chatzipli A,  Hardy C,  Whalley C,  Wu C-H,  Beggs A,  McDermott U,  Dunne P,  Meade A,  Walker S,  Murray G,  Samuel L,  Seymour M,  Tomlinson I,  Quirke P,  Maughan T,  Rittscher J,  Koelzer V,  on behalf of S:CORT consortium ,  et al. (2019)
Characterization of Biological Motion Using Motion Sensing Superpixels.
Zhou FY,  Ruiz-Puig C,  Owen RP,  White MJ,  Rittscher J,  Lu X,  et al. (2019)
GCT-07 Moving to a digital pathology supraregional germ cell tumour service
Browning L,  Colling R,  White K,  Rittscher J,  Roskell D,  Hemsworth H,  Soares M,  Roberts ISD,  Royston D,  Rees G,  Turner G,  Fryer E,  Roberts-Gant S,  Siiankoski D,  Bryant RJ,  Molyneux A,  Taibi A,  Johnson E,  Protheroe A,  Tuthill M,  Sullivan M,  Verrill C,  et al. (2019)
Discovery of rare phenotypes in cellular images using weakly supervised deep learning
Sailem H,  Arias-Garcia M,  Bakal C,  Zisserman A,  Rittscher J,  et al. (2018)
Sensorless adaptive optics for isoSTED nanoscopy
Antonello J,  Hao X,  Allgeyer ES,  Bewersdorf J,  Rittscher J,  Booth MJ,  et al. (2018)
Improving whole slide segmentation through visual context: a systematic study
Sirinukunwattana K,  Khalid Alham N,  Verrill C,  Rittscher J,  et al. (2018)
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. (2018)
Pathologist Assessment of Novel Histological Features in Prostate Cancer
Tupper PM,  Rao S,  Bryant R,  Lamb A,  Hamdy F,  Tomlinson I,  Sirinukunwattana K,  Alham NK,  Rittscher J,  Verrill C,  et al. (2018)
Analysis of live cell images: methods, tools and opportunities
Nketia T,  Sailem H,  Rohde G,  Machiraju R,  Rittscher J,  et al. (2017)
Digital analysis of tumour microarchitecture as an independent prognostic tool in breast cancer
Roxanis I,  Colling R,  Rakha EA,  Green A,  Rittscher J,  Conceicao RC,  Ross A,  Nicholson G,  Holmes C,  et al. (2017)
Digital analysis of tumour microarchitecture as an independent prognostic tool in breast cancer
Roxanis I,  Colling R,  Rakha EA,  Green A,  Rittscher J,  Conceicao RC,  Ross A,  Nicholson G,  Holmes C,  et al. (2017)
CELL SEGMENTATION AND CLASSIFICATION BY HIERARCHICAL SUPERVISED SHAPE RANKING
Santamaria-Pang A,  Rittscher J,  Gerdes M,  Padfield D,  et al. (2015)
Welcome letter
Angelini E,  Kovačević J,  Ourselin S,  Rittscher J,  et al. (2015)
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,  Bello M,  Ginty F,  Sevinsky C,  Li Q,  Rothney M,  Sarachan B,  et al. (2015)
MAPPING FOR TISSUE BASED CYTOMETRY
Rittscher J,  Santamaria-Pang A,  et al. (2014)
Epithelial cell segmentation via shape ranking
Santamaria-Pang A,  Huang Y,  Pang Z,  Qing L,  Rittscher J,  et al. (2014)
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.
Gerdes MJ,  Sevinsky CJ,  Sood A,  Adak S,  Bello MO,  Bordwell A,  Can A,  Corwin A,  Dinn S,  Filkins RJ,  Hollman D,  Kamath V,  Kaanumalle S,  Kenny K,  Larsen M,  Lazare M,  Li Q,  Lowes C,  McCulloch CC,  McDonough E,  Montalto MC,  Pang Z,  Rittscher J,  Santamaria-Pang A,  Sarachan BD,  Seel ML,  Seppo A,  Shaikh K,  Sui Y,  Zhang J,  Ginty F,  et al. (2013)
CELL SEGMENTATION AND CLASSIFICATION VIA UNSUPERVISED SHAPE RANKING
Santamaria-Pang A,  Huang Y,  Rittscher J,  et al. (2013)
Digitally adjusting chromogenic dye proportions in brightfield microscopy images.
Bilgin CC,  Rittscher J,  Filkins R,  Can A,  et al. (2012)
TISSUE SEGMENTATION AND CLASSIFICATION USING GRAPH-BASED UNSUPERVISED CLUSTERING
Margolis D,  Santamaria-Pang A,  Rittscher J,  et al. (2012)
Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis.
Padfield D,  Rittscher J,  Roysam B,  et al. (2011)
Non-parametric population analysis of cellular phenotypes.
Singh S,  Janoos F,  Pécot T,  Caserta E,  Huang K,  Rittscher J,  Leone G,  Machiraju R,  et al. (2011)
Identifying nuclear phenotypes using semi-supervised metric learning.
Singh S,  Janoos F,  Pécot T,  Caserta E,  Leone G,  Rittscher J,  Machiraju R,  et al. (2011)
METHODS AND ALGORITHMS FOR EXTRACTING HIGH-CONTENT SIGNATURES FROM CELLS, TISSUES, AND MODEL ORGANISMS
Rittscher J,  Padfield D,  Santamaria A,  Tu J,  Can A,  Bello M,  Gao D,  Sood A,  Gerdes M,  Ginty F,  et al. (2011)
QUANTITATIVE BIOLOGICAL STUDIES ENABLED BY ROBUST CELL TRACKING
Padfield D,  Rittscher J,  Roysam B,  et al. (2011)
Non-parametric population analysis of cellular phenotypes
Singh S,  Janoos F,  Pécot T,  Caserta E,  Huang K,  Rittscher J,  Leone G,  Machiraju R,  et al. (2011)
Identifying nuclear phenotypes using semi-supervised metric learning
Singh S,  Janoos F,  Pécot T,  Caserta E,  Leone G,  Rittscher J,  Machiraju R,  et al. (2011)
LPSM: Fitting shape model by linear programming
Tu J,  Laflen B,  Liu X,  Bello M,  Rittscher J,  Tu P,  et al. (2011)
Appearance-based person reidentification in camera networks: problem overview and current approaches
Doretto G,  Sebastian T,  Tu P,  Rittscher J,  et al. (2011)
Automated training data generation for microscopy focus classification.
Gao D,  Padfield D,  Rittscher J,  McKay R,  et al. (2010)
Automated training data generation for microscopy focus classification
Gao D,  Padfield D,  Rittscher J,  McKay R,  et al. (2010)
ANALYSIS OF SPATIAL VARIATION OF NUCLEAR MORPHOLOGY IN TISSUE MICROENVIRONMENTS
Singh S,  Raman S,  Caserta E,  Leone G,  Ostrowski M,  Rittscher J,  Machiraju R,  et al. (2010)
Automated System and method for screening zebrafish
Rittscher J,  Yekta A,  Bello M,  Tu J,  Seng W,  et al. (2009)
Spatio-temporal cell cycle phase analysis using level sets and fast marching methods.
Padfield D,  Rittscher J,  Thomas N,  Roysam B,  et al. (2009)
Coupled minimum-cost flow cell tracking.
Padfield D,  Rittscher J,  Roysam B,  et al. (2009)
A model change detection approach to dynamic scene modeling
Kim SJ,  Doretto G,  Rittscher J,  Tu P,  Krahnstoever N,  Pollefeys M,  et al. (2009)
Coupled minimum-cost flow cell tracking
Padfield D,  Rittscher J,  Roysam B,  et al. (2009)
Unified Crowd Segmentation
Tu P,  Sebastian T,  Doretto G,  Krahnstoever N,  Rittscher J,  Yu T,  et al. (2008)
METHODS FOR MONITORING CELLULAR MOTION AND FUNCTION
Padfield D,  Rittscher J,  Roysam B,  et al. (2008)
Spatio-temporal cell segmentation and tracking for automated screening
Padfield D,  Rittscher J,  Roysam B,  et al. (2008)
Microscopic Image Analysis for Life Science Applications
Rittscher J,  Machiraju R,  Wong STC,  et al. (2008)
View adaptive detection and distributed site wide tracking
Tu P,  Krahstoever N,  Rittscher J,  et al. (2007)
Shape and appearance context modeling
Wang X,  Doretto G,  Sebastian T,  Rittscher J,  Tu P,  et al. (2007)
An intelligent video framework for homeland protection
Tu PH,  Doretto G,  Krahnstoever NO,  Perera AGA,  Wheeler FW,  Liu X,  Rittscher J,  Sebastian TB,  Yu T,  Harding KG,  et al. (2007)
Multi-target tracking using hybrid particle filtering
Rittscher J,  Krahnstoever N,  Galup L,  et al. (2007)
Surveillance video analytics for large camera networks
Tu P,  Wheeler F,  Krahnstoever N,  Sebastian T,  Rittscher J,  Liu X,  Perera A,  Doretto G,  et al. (2007)
Optimal pose for face recognition
Liu X,  Chen T,  Rittscher J,  et al. (2006)
Person reidentification using spatiotemporal appearance
Gheissari N,  Sebastian TB,  Tu PH,  Rittscher J,  Hartley R,  et al. (2006)
Validation methods for cell cycle analysis algorithms in confocal fluorescence images
Padfield D,  Rittscher J,  Thomas N,  Roysam B,  et al. (2006)
Computing pragocytosis index for high-throughput applications
Sebastian T,  Rittscher J,  Yu L,  et al. (2006)
Potential analysis made by oneself
Keller M,  Rittscher J,  et al. (2006)
Activity recognition using visual tracking and RFID
Krahnstoever N,  Rittscher J,  Tu P,  Chean K,  Tomlinson T,  et al. (2005)
Detecting and counting people in surveillance applications
Liu X,  Tu PH,  Rittscher TJ,  Perera A,  Krahnstoever N,  et al. (2005)
Simultaneous estimation of segmentation and shape
Rittscher J,  Tu PH,  Krahnstoever N,  et al. (2005)
Disturbance management in large logistics networks
Hinrichs J,  Rittscher J,  Laakmann F,  Hellingrath B,  et al. (2005)
Foreign object detection and quantification of fat content using a novel multiplexing electric field sensor
Rittscher A,  Sulaimalebbe A,  Capdeboscq Y,  Rittscher J,  et al. (2005)
Identification
Kelliher TP,  Rittscher J,  Tu P,  et al. (2005)
Identification
Tu P,  Kelliher TP,  Rittscher J,  et al. (2005)
Crowd segmentation through emergent labeling
Tu PH,  Rittscher J,  et al. (2004)
Collaborative ramp-up planning and controlling
Hinrichs J,  Rittscher J,  Laakmann F,  Hellingrath B,  et al. (2004)
Mathematical modelling of animate and intentional motion.
Rittscher J,  Blake A,  Hoogs A,  Stein G,  et al. (2003)
Video content annotation using visual analysis and a large semantic knowledgebase
Hoogs A,  Rittscher J,  Stein G,  Schmiederer J,  et al. (2003)
Site calibration for large indoor scenes
Tu P,  Rittscher J,  Kelliher T,  et al. (2003)
Towards the automatic analysis of complex human body motions
Rittscher J,  Blake A,  Roberts SJ,  et al. (2002)
An HMM-based segmentation method for traffic monitoring movies
Kato J,  Watanabe T,  Joga S,  Rittscher J,  Blake A,  et al. (2002)
Guiding random particles by deterministic search
Sullivan J,  Rittscher J,  et al. (2001)
Learning and classification of complex dynamics
North B,  Blake A,  Isard M,  Rittscher J,  et al. (2000)
An integral criterion for detecting boundary edges and textured regions
Rittscher J,  Sullivan J,  et al. (2000)
Statistical foreground modelling for object localisation
Sullivan J,  Blake A,  Rittscher J,  et al. (2000)
A probabilistic background model for tracking
Rittscher J,  Kato J,  Joga S,  Blake A,  et al. (2000)
Classification of human body motion
Rittscher J,  Blake A,  et al. (1999)
Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detection
Chowdhury T,  Bajwa ARS,  Chakraborti T,  Rittscher J,  Pal U,  et al. ()
Early Detection of Liver Fibrosis Using Graph Convolutional Networks
Wojciechowska M,  Malacrino S,  Martin NG,  Fehri H,  Rittscher J,  et al. ()
Artificial Intelligence for Advance Requesting of Immunohistochemistry in Diagnostically Uncertain Prostate Biopsies
Chatrian A,  Colling R,  Browning L,  Alham NK,  Sirinukunwattana K,  Malacrino S,  Haghighat M,  Aberdeen A,  Monks A,  Moxley-Wyles B,  Rakha E,  Snead D,  Rittscher J,  Verrill C,  et al. ()
Tracking exocytic vesicle movements reveals the spatial control of secretion in epithelial cells
Richens JH,  Dmitrieva M,  Zenner HL,  Muschalik N,  Butler R,  Glashauser J,  Camelo C,  Luschnig S,  Munro S,  Rittscher J,  St Johnston D,  et al. ()
Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.
Hu Y,  Sirinukunwattana K,  Li B,  Gaitskell K,  Domingo E,  Bonnaffé W,  Wojciechowska M,  Wood R,  Alham NK,  Malacrino S,  Woodcock DJ,  Verrill C,  Ahmed A,  Rittscher J,  et al. ()
Enhancing Liver Fibrosis Measurement: Deep Learning and Uncertainty Analysis Across Multi-Centre Cohorts
Wojciechowska M,  Malacrino S,  Windell D,  Culver EL,  Dyson JK,  Rittscher J,  et al. ()
Enhancing Liver Fibrosis Measurement: Deep Learning and Uncertainty Analysis Across Multi-Centre Cohorts
Wojciechowska M,  Malacrino S,  Windell D,  Culver E,  Dyson J,  Rittscher J,  et al. ()