Sidhart Sami, Ali Sharjeel, Sri Atluri, Miao Zhao, Caroline Roney, Eirini Marouli, Shaheer U. Saeed · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31253 · open-access PDF
A visibilidade limitada de tumores em imagens intraoperatórias complica a navegação cirúrgica, incluindo carcinoma hepatocelular (HCC) visando tomografia computadorizada (CT). Isto torna os conjuntos de dados rotulados difíceis de curar para o aprendizado profundo, e a transferência de delineamentos pré-operatórios através do registro permanece desafiadora devido à deformação intraoperatória e à falta de dados pré- e intraoperatórios emparelhados. Propomos transferir as aparências de tumores aprendidas a partir de imagens de ressonância magnética pré-operatória (MR) para orientar a localização na CT intraoperatória através de supervisão fraca.
Machine translation (Meta M2M100); the English original follows.
Limited tumour visibility on intra-operative images complicates surgical navigation, including liver hepatocellular carcinoma (HCC) targeting on computed tomography (CT) imaging. This makes labelled datasets difficult to curate for deep learning, and transferring pre-operative delineations through registration remains challenging due to intra-operative deformation and lack of paired pre- and intra-operative data. We propose to transfer tumour appearances learned from pre-operative magnetic resonance (MR) images to guide localisation on intra-operative CT through weak supervision. A classifier
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