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

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

T<sub>2</sub>-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 nove...

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Bibliographic Details
Main Authors: Reza Kalantar, Sebastian Curcean, Jessica M. Winfield, Gigin Lin, Christina Messiou, Matthew D. Blackledge, Dow-Mu Koh
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Diagnostics
Subjects:
tumor segmentation
multiparametric MRI
cervical cancer
deep learning
dilated convolution
radiology
Online Access:https://www.mdpi.com/2075-4418/13/21/3381

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https://www.mdpi.com/2075-4418/13/21/3381

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