Brain Tumor Detection and Classification Using Cycle Generative Adversarial Networks-Reference-Cited by-同舟云学术

Brain Tumor Detection and Classification Using Cycle Generative Adversarial Networks

Published:2022-02-09 Issue:2 Volume:14 Page:485-502
ISSN:1913-2751
Container-title:Interdisciplinary Sciences: Computational Life Sciences
language:en
Short-container-title:Interdiscip Sci Comput Life Sci

Author:

Gupta Rajeev Kumar^ORCID,Bharti Santosh,Kunhare Nilesh,Sahu Yatendra,Pathik Nikhlesh

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Computer Science Applications,General Biochemistry, Genetics and Molecular Biology

Link

https://link.springer.com/content/pdf/10.1007/s12539-022-00502-6.pdf

Reference35 articles.

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2. Mazurowski MA, Buda M, Saha A, Bashir MR (2019) Deep learning in radiology: an overview of the concepts and a survey of the state of the art with focus on MRI. J Magn Reson Imaging 49:939–954. https://doi.org/10.1002/jmri.26534

3. Hussain UN et al (2020) A unified design of ACO and skewness based brain tumor segmentation and classification from MRI scans. J Control Eng Appl Inf 22:43–55

4. Pereira S, Pinto A, Alves V, Silva CA (2016) Brain tumor segmentation using convolutional neural networks in MRI images. IEEE Trans Med Imaging 35(5):1240–1251. https://doi.org/10.1109/TMI.2016.2538465

5. Bansal S, Kaur S, Kaur N (2019) Enhancement in brain image segmentation using swarm ant lion algorithm. IJITEE 8(10):1623–1628

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