Modified U-Net Architeture based Ischemic Stroke Lesions Segmentation-Reference-Cited by-同舟云学术

Modified U-Net Architeture based Ischemic Stroke Lesions Segmentation

Published:2022-12-19 Issue: Volume: Page:
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Container-title:2022 IEEE 21st international Ccnference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)
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Author:

Abdmouleh Nabil¹,Echtioui Amira¹,Kallel Fathi¹,Hamida Ahmed Ben²

Affiliation:

1. Advanced Technologies for Medicine and Signals, ENIS,Sfax University,ATMS Lab,Sfax,Tunisia

2. College of Computer Science King Khaled University ‘KKU’,Department IS,KSA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10018923/10018970/10019136.pdf?arnumber=10019136

Reference11 articles.

1. Multiscale 3D convolutional neural networks for lesion segmentation in brain MRI;kamnitsas;Proc MICCAI Ischemic Stroke Lesion Segmentation Challenge,0

2. Improved Adam Optimizer for Deep Neural Networks

3. Automatic Detection of Ischemic Stroke Lesion from Multimodal MR Image

4. Ischemic stroke lesion segmentation using local gradient and texture features;reza;Ischemic Stroke Lesion Segmentation,2015

5. Perfusion Computed Tomography for the Evaluation of Acute Ischemic Stroke

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1. Enhanced Ischemic Stroke Lesion Segmentation in MRI Using Attention U-Net with Generalized Dice Focal Loss;Applied Sciences;2024-09-11

2. MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024