Titlebook: Deep Generative Models; 4th MICCAI Workshop, Anirban Mukhopadhyay,Ilkay Oksuz,Yixuan Yuan Conference proceedings 2025 The Editor(s) (if app

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,Einstimmen in das Arbeitsfeld der Führung,rasts, and appearances of anatomical structures. We introduce compositionality as an inductive bias in a cross-modal segmentation network to improve segmentation performance and interpretability while reducing complexity. The proposed network is an end-to-end cross-modal segmentation framework that

Kidney-Failure

Die drei Regeln der Erkenntnisoffenheit,ge. We propose a microscopy pseudo labeling pipeline utilizing unsupervised image translation to address this issue. Our method generates pseudo labels by translating between labeled and unlabeled domains without requiring prior annotation in the target domain. We evaluate two pseudo labeling strate

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Fallbeispiele zu Rollenbildern, volumetric changes. However, many of the evaluation tools are optimized for analyzing healthy tissue. To enable the evaluation of scans containing pathological tissue, it is therefore required to restore healthy tissue in the pathological areas. In this work, we explore and extend denoising diffusi

ASTER

Warum Stellenbeschreibungen/Rollenbilder?, who often review hundreds of mammograms daily, leading to overdiagnosis and overtreatment. Computer-Aided Diagnosis (CAD) systems have been developed to assist in this process, but their capabilities, particularly in lesion segmentation, remained limited. With the contemporary advances in deep lear

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