Znet: Deep Learning Approach for 2D MRI Brain Tumor Segmentation-Reference-Cited by-同舟云学术

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Znet: Deep Learning Approach for 2D MRI Brain Tumor Segmentation

Published:2022 Issue: Volume:10 Page:1-8
ISSN:2168-2372
Container-title:IEEE Journal of Translational Engineering in Health and Medicine
language:
Short-container-title:IEEE J. Transl. Eng. Health Med.

Author:

Ottom Mohammad Ashraf¹^ORCID,Rahman Hanif Abdul²^ORCID,Dinov Ivo D.²^ORCID

Affiliation:

1. Department of Information Systems, Yarmouk University, Irbid, Jordan

2. Departments of Health Behavior and Biological Sciences and Computational Medicine and Bioinformatics, Statistics Online Computational Resource, University of Michigan, Ann Arbor, MI, USA

Funder

NSF grants

Fulbright Association

NIH grants

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Medicine

Link

https://ieeexplore.ieee.org/ielam/6221039/9652399/9779760-aam.pdf

Reference40 articles.

1. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

2. A survey of loss functions for semantic segmentation

3. A comprehensive survey of recent trends in deep learning for digital images augmentation

4. Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm

5. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

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