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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Bibliografische Detailangaben

Hauptverfasser:	Amene Vatanparast, Mansoor Fateh, Hoda Mashayekhi, Saideh Ferdowsi
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Nature Portfolio 2025-12-01
Schriftenreihe:	Scientific Reports
Schlagworte:	Fetal cerebellar segmentation Ultrasound image Semi-supervised learning Convolution neural network Attention block Squeeze-and-excitation block
Online-Zugang:	https://doi.org/10.1038/s41598-025-28201-4
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