Medical Image Segmentation

While state-of-the-art automated models for medical image segmentation achieve high mean performance, they frequently suffer from localized, catastrophic failures that preclude safe clinical deployment, particularly in n…

Medical Image Segmentation Interactive Segmentation

LightMIS: Ultra-Lightweight Medical Image Segmentation Without a Stage-Wise Decoder

2026-09-24 · Andrei Arhire, Mihaela-Elena Breabăn, Radu Timofte hf

We present LightMIS, a scalable family of ultra-lightweight convolutional networks for 2D binary medical image segmentation without a learned stage-wise decoder. LightMIS aligns the outputs of a five-level encoder to a c…

Medical Image Segmentation

De-GAN - Dynamic Parameter Tuned GAN for 3D Medical Image Segmentation: A Step Towards Generalisation

2026-09-15 · Zoha Usama, Azadeh Alavi arxiv

Brain tumor segmentation remains difficult because enhancing tumor (ET) has low contrast and overlaps surrounding tissue, while scanner and site variation causes domain shift. We propose DE-GAN, a contrast-enhancing cond…

Medical Image Segmentation Brain Tumor Segmentation

When Fusion Fails: Corruption-Aware Rebalanced Fusion for Multi-Modal Medical Image Segmentation

2026-09-09 · Yuchen Pei, Xiaoyu Hu, Yixiong Zou, Dingwen Hu 외 arxiv

Multi-modal medical image segmentation leverages complementary diagnostic information, yet fusion can underperform single-modality baselines when spatially aligned inputs differ in quality. Here, "corruption" primarily d…

Medical Image Segmentation

From Few-Shot Segmentation to Clinician-in-the-Loop Medical Image Analysis

2026-09-09 · Yazhou Zhu arxiv

Few-shot medical image segmentation (FSMIS) seeks to delineate unseen structures from a small support set, but its standard formulation fixes task-defining evidence before inference. This assumption is fragile when query…

Medical Image Segmentation Interactive Segmentation Test-time Adaptation

LightMedSeg-ISLES: Stroke Lesion Segmentation with 81x Fewer Parameters than nnU-Net

2026-09-09 · Giorgi Nikvashvili, Hanxue Gu, Jie Bao, Kang Wang 외 arxiv

Large networks and ensembles often lead medical image segmentation challenges, but their storage and inference demands complicate deployment. We present LightMedSeg-ISLES, a 1.26-million-parameter pipeline for T1-weighte…

Medical Image Segmentation Lesion Segmentation

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