Diagnostic Performance of a Deep Learning-Based Tool for the Detection and Staging of Rectal Cancers on Endoscopic Ultrasound: Prospective Study

<b>Background</b>: Loco-regional staging of rectal cancer relies on MRI and rectal EUS (R-EUS). In situ and T1 tumors may be candidates for endoscopic resection, and R-EUS enables reliable differentiation among early-stage tumors (Tis, T1, T2), a distinction that MRI cannot consistently provide. Thi...

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Detalhes bibliográficos

Principais autores:	Amedeo Montale, Marco Valvano, Andrea Ghezzi, Marco Magliocco, Nicola Panvini, Mariangela Rutigliani, Massimo Oppezzi, Lucio Molini, Francesco Paparo
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Diagnostics
Assuntos:	rectal endoscopic ultrasound transrectal ultrasound rectal cancer deep learning artificial intelligence computer-aided detection
Acesso em linha:	https://www.mdpi.com/2075-4418/16/8/1161
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