Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet-Reference-Cited by-同舟云学术

Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet

Published:2023-10-20 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Samudrala Suresh,Mohan C. Krishna

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-17411-5.pdf

Reference39 articles.

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3. Zebari DA, Zeebaree DQ, Abdulazeez AM, Haron H, Hamed HNA (2020) Improved threshold based and trainable fully automated segmentation for breast cancer boundary and pectoral muscle in mammogram images. IEEE Access 8(1):203097–203116

4. Zohair AA, Shamil AA, Sulong G (2015) Latest methods of image enhancement and restoration for computed tomography: a concise review. Appl Med Inform 36(1):1–12

5. Acharya A, Giri AV (2020) Contrast improvement using local gamma correction. In: 2020 6th international conference on advanced computing and communication systems (ICACCS), Coimbatore, India, pp 110–114

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