Article

Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

2025-11-23

Abstract excerpt

<h4>Introduction</h4> Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art models remain task-specific and data-hungry. The recent emergence of powerful, multimodal large language models (LLMs) presents a generalizable option; however, their efficacy in the specialized medical domain remains largely unquantified. We aim to benchmark the foundational Gemini 2.5 Flash and...

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Radiomics and Machine Learning in Medical Imaging

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Literature Corpus work: fecd3756-d894-57d2-a196-0ed13ae98263
DOI: 10.1101/2025.11.21.25340008

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