Segmentation and Classification of Gastric Cancer from Endoscopic Image Dataset with the Aid of Artificial Intelligence-Reference-Cited by-同舟云学术

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Segmentation and Classification of Gastric Cancer from Endoscopic Image Dataset with the Aid of Artificial Intelligence

Published:2023-11-22 Issue: Volume: Page:212-218
ISSN:
Container-title:2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA)
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Author:

Anitha Cuddapah¹,Srinivas Rao Vemu²,R Ramyadevi.³,R Maya.⁴,Debroy Subhasish⁵,R Mahaveerakannan⁶

Affiliation:

1. School of Computing, Mohan Babu University, Sree Vidyanikethan Engineering College,Tirupati,Andhra Pradesh,517102

2. Shri Vishnu Engineering College for Women,Bhimavaram,Andhra Pradesh

3. Saveetha Engineering College,Department of Computer Science & Engineering

4. Chennai Institute of Technology & Applied Research,Department of Electrical & Electronics Engineering

5. Dr. B.C. Roy Engineering College,Durgapur,West Bengal

6. Saveetha School of Engineering, SIMETs,Department of Computer Science and Engineering,Chennai,Tamil Nadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10394672/10394681/10394686.pdf?arnumber=10394686

Reference24 articles.

1. Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

2. Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning

3. Current status and future perspective of artificial intelligence applications in endoscopic diagnosis and management of gastric cancer

4. Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study

5. Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

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