Temporal dependency modeling for improved medical image segmentation: The R-UNet perspective

Temporal dependency modeling for improved medical image segmentation: The R-UNet perspective

In this study, we propose a modified version of the widely used UNet architecture, enhanced by the integration of recurrent blocks at each step of the encoder (down-sampling) and decoder (up-sampling) stages. The proposed Recurrent UNet (R-UNet) architecture aims to improve the performance of semant...

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Bibliographic Details
Main Authors: Ahmed Alweshah, Roohollah Barzamini, Farshid Hajati, Shoorangiz Shams Shamsabad Farahani, Mohammad Arabian, Behnaz Sohani
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Franklin Open
Subjects:
Machine learning
Medical image processing
R-UNet
Deep learning
Recurrent neural network
CNN
Online Access:http://www.sciencedirect.com/science/article/pii/S2773186324001129
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