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20212026
most citedMultimodal PET/CT Tumour Segmentation and Prediction of Progression-Free Survival using a Full-Scale UNet with Attention

1 citations · 2 across the 13 of their papers we have counts for

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cs.CV2026

Deep Auxiliary Learning via Bilevel Feature Optimization for Label-Efficient Medical Image Segmentation

Fuping Wu, Xi Jia, Le Zhang +4

Auxiliary learning (AL), which can improve the performance of a primary task by leveraging related auxiliary tasks, is commonly regarded as a special case of multi-task learning. E…

cs.CV2026

Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models

Michalis Pistos, Bartłomiej W. Papież

Foundation models are increasingly used as feature extractors for downstream tasks with limited data, typically through representations obtained from their encoders. However, found…

cs.CV2026

When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation

Jack A. Johnson, Bartłomiej W. Papież

PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour phenotypes that may be missed by ei…

cs.CV2026

Evaluation of Clinically Steerable Retinal Image Generation from Foundation Model Latent Spaces

Zuzanna A. Wakefield-Skórniewska, Bartłomiej W. Papież

Medical foundation models learn latent representations of clinically meaningful phenotypes, yet their ability to support controllable image generation remains largely unexplored. W…

cs.CV2026

WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance

Xin Tian, Xudong Ma, Tianqi Yang +4

We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulties: (i) severe class imbalan…

cs.CV2024

TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation

Santosh Sanjeev, Fadillah Adamsyah Maani, Arsen Abzhanov +4

With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-ra…

cs.CV2022★ 1 cited

An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images

Yuhan Zheng, Fuping Wu, Bartłomiej W. Papież

Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usuall…