IFAS: improved fully automatic segmentation convolutional neural network model along with morphological segmentation for brain tumor detection-Reference-Cited by-同舟云学术

IFAS: improved fully automatic segmentation convolutional neural network model along with morphological segmentation for brain tumor detection

Published:2023-10-14 Issue: Volume: Page:
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Kulshreshtha Akanksha^ORCID,Nagpal Arpita

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s41870-023-01572-5.pdf

Reference35 articles.

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2. Bao S, Chung AC (2018) Multi-scale structured CNN with label consistency for brain MR image segmentation. Comput Methods Biomech Biomed Eng Imaging & Vis 6(1):113–117

3. Amin J, Sharif M, Yasmin M, Fernandes SL (2020) A distinctive approach in brain tumor detection and classification using MRI. Pattern Recogn Lett 139:118–127

4. Talo M, Yildirim O, Baloglu UB, Aydin G, Acharya UR (2019) Convolutional neural networks for multi-class brain disease detection using MRI images. Comput Med Imaging Graph 78:101673

5. Çinar A, Yildirim M (2020) Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture. Med Hypotheses 139:109684

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