Jens Rittscher
Professor of Engineering Science
Develops image analysis and machine learning for computational pathology and cancer research.
Jens Rittscher's lab at Oxford works on medical imaging & healthcare AI and medical image analysis. 18 papers since 2023, 4 at top venues, mostly ISBI and MICCAI. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 22%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 1 · collecting
- 4 papers2025 · T1 1
- 7 papers2024 · T1 1
- 3 papers2023 · T1 1
T1 venuesOtherVenues: ISBI, MICCAI
Research focuspaper titles that use each topic's words
- Medical image analysis4 papers
- pathology2 papers
- cancer2 papers
- Medical imaging & healthcare AI1 paper
- computational pathology1 paper
Paper list
From DBLP.
20264 papers
- ISBIDistilling Knowledge from Multiple Foundation Models for Accurate and Efficient Spatial Gene Expression Prediction (opens in a new tab)
- MICCAI (T1)Harnessing Adversarial Distillation to Customise Debiased, Disease-Specific Pathology Foundation Models for Breast Cancer (opens in a new tab)
- ISBIPatchsurg: Leveraging Synthetic Datasets for High-Fidelity Depth Estimation in Surgery (opens in a new tab)
- IEEE Trans. Medical ImagingSelf-Supervised Monocular Depth and Pose Estimation for Endoscopy With Latent Priors (opens in a new tab)
20254 papers
- DGM4MICCAI@MICCAICtrlEndoDiff: Diffusion-Based Synthetic Image Generation for Enhanced ACF Segmentation (opens in a new tab)
- Medical Image Anal.Editorial for Special Issue on Foundation Models for Medical Image Analysis (opens in a new tab)
- Medical Image Anal.Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology (opens in a new tab)
- MICCAI (T1)Unsupervised Discovery of Spatiotypes and Context-Aware Graph Neural Networks for Modeling Clinical Endpoints (opens in a new tab)
20247 papers
- ISBIAccurate Subtyping of Lung Cancers by Modelling Class Dependencies (opens in a new tab)
- ISBICharacterising borderline areas in bladder tumour grading with Bayesian graph neural networks (opens in a new tab)
- CVPR WorkshopCluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images (opens in a new tab)
- DEMI@MICCAIEvaluating Histopathology Foundation Models for Few-Shot Tissue Clustering: An Application to LC25000 Augmented Dataset Cleaning (opens in a new tab)
- MICCAI (T1)MultiVarNet - Predicting Tumour Mutational Status at the Protein Level (opens in a new tab)
- CVPR WorkshopRefining Biologically Inconsistent Segmentation Masks with Masked Autoencoders (opens in a new tab)
- IEEE Trans. Medical ImagingSSL-CPCD: Self-Supervised Learning With Composite Pretext-Class Discrimination for Improved Generalisability in Endoscopic Image Analysis (opens in a new tab)
20233 papers
- IEEE Trans. Neural Networks Learn. Syst.FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation (opens in a new tab)
- MICCAI (T1)Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies (opens in a new tab)
- ISBILeveraging Inter-Annotator Disagreement for Semi-Supervised Segmentation (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Your notes
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
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