Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network

Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network

This work presents a deep-learning-based denoising technique to accelerate the acquisition of high <i>b</i>-value diffusion-weighted MRI for rectal cancer. A denoising convolutional neural network (DCNN) with a combined L1–L2 loss function was developed to denoise high <i>b</i&g...

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Bibliographic Details
Main Authors: Mohaddese Mohammadi, Elena A. Kaye, Or Alus, Youngwook Kee, Jennifer S. Golia Pernicka, Maria El Homsi, Iva Petkovska, Ricardo Otazo
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Bioengineering
Subjects:
diffusion-weighted MRI
rectal cancer
deep learning
denoising
Online Access:https://www.mdpi.com/2306-5354/10/3/359

Internet

https://www.mdpi.com/2306-5354/10/3/359

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