An interpretable deep stacked autoencoder architecture for rapid convergence and robust genetic disorder detection from fetal ultrasound images

Early and reliable detection of fetal genetic disorders (FGD) using prenatal ultrasound (US) imaging is crucial for timely treatment intervention and improved postpartum outcomes. US images are inherently affected by speckle noise, reduced contrast, and subtle anatomical variations, which impede aut...

Descripció completa

Dades bibliogràfiques

Autors principals:	A. Anitha, S. Balaji
Format:	Artigo
Idioma:	Inglês
Publicat:	PeerJ Inc. 2026-07-01
Col·lecció:	PeerJ Computer Science
Matèries:	Ultrasound images Segmentation-aware explainable AI network Autoencoder Deep learning Fetal genetic disorders Contrast-limited adaptive histogram equalization
Accés en línia:	https://peerj.com/articles/cs-3998.pdf
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!