Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging

T₂-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) are essential components of cervical cancer diagnosis. However, combining these channels for the training of deep learning models is challenging due to image misalignment. Here, we propose a novel multi-head...

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Principais autores:	Reza Kalantar, Sebastian Curcean, Jessica M. Winfield, Gigin Lin, Christina Messiou, Matthew D. Blackledge, Dow-Mu Koh
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2023-11-01
Series:	Diagnostics
Assuntos:	tumor segmentation multiparametric MRI cervical cancer deep learning dilated convolution radiology
Acceso en liña:	https://www.mdpi.com/2075-4418/13/21/3381
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