Automatic and Robust Segmentation of Multiple Sclerosis Lesions with Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Automatic and Robust Segmentation of Multiple Sclerosis Lesions with Convolutional Neural Networks

Published:2020 Issue:1 Volume:66 Page:977-991
ISSN:1546-2226
Container-title:Computers, Materials & Continua
language:en
Short-container-title:

Author:

M. Rehan Afzal H.,Luo Suhuai,Ramadan Saadallah,Lechner-Scott Jeannette,Ruhul Amin Mohammad,Li Jiaming,Kamran Afzal M.

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Modelling and Simulation,Biomaterials

Link

https://www.techscience.com/cmc/v66n1/40492/pdf

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient segmentation of active and inactive plaques in FLAIR-images using DeepLabV3Plus SE with efficientnetb0 backbone in multiple sclerosis;Scientific Reports;2024-07-15

2. Deep Learning-based Methods for MS Lesion Segmentation: A Review;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11

3. A Hybrid Method for Multiple Sclerosis Lesion Segmentation Using Wavelet and Dense U-Net;International Journal of Computational Intelligence and Applications;2024-04-25

4. Brain hyperintensities: automatic segmentation of white matter hyperintensities in clinical brain MRI images using improved deep neural network;The Journal of Supercomputing;2024-04-04

5. Diagnostic effectiveness of deep learning-based MRI in predicting multiple sclerosis: A meta-analysis;Neurosciences;2024-04

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