SS_CASE_UNet: an attention-enhanced semi-supervised framework for fetal cerebellum segmentation in ultrasound images

Abstract Accurate segmentation of the fetal cerebellum in ultrasound images is crucial for assessing fetal development and detecting prenatal abnormalities. However, this task remains challenging due to factors such as image noise, complex anatomical structures, and limited availability of annotated...

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Bibliografiske detaljer

Principais autores:	Amene Vatanparast, Mansoor Fateh, Hoda Mashayekhi, Saideh Ferdowsi
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2025-12-01
Serier:	Scientific Reports
Fag:	Fetal cerebellar segmentation Ultrasound image Semi-supervised learning Convolution neural network Attention block Squeeze-and-excitation block
Online adgang:	https://doi.org/10.1038/s41598-025-28201-4
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