Machine Learning Approach for Detecting Liver Tumours in CT images using the Gray Level Co-Occurrence Metrix-Reference-Cited by-同舟云学术

Machine Learning Approach for Detecting Liver Tumours in CT images using the Gray Level Co-Occurrence Metrix

Published:2023-06-16 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC)
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Author:

Aruna S¹,Saranya A.²,Guru Pandi D³,Kavya S. P.⁴,Pareek Piyush Kumar⁵

Affiliation:

1. Computational Intelligence SRMIST,Chennai,India

2. SRMIST,Computational Intelligence Department,Chennai,India

3. Panimalar Engineering College,Department of ECE,Chennai,India

4. KPR Institute of Engineering and Technology,Department of Artificial Intelligence and Data Science,Arasur,India

5. Nitte Meenakshi Institute of Technology,Department of AI and ML,Bengaluru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199108/10199167/10199347.pdf?arnumber=10199347

Reference15 articles.

1. Modified U-Net for liver cancer segmentation from computed tomography images with a new class balancing method

2. Delineation of ischemic lesion from brain MRI using attention gated fully convolutional network

3. Ensembled liver cancer detection and classification using CT images;krishan;Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine,2020

4. A comprehensive survey of recent trends in deep learning for digital images augmentation;khalifa;Artificial Intelligence Review,2021

5. Automatic liver and tumour segmentation from CT images using Deep learning algorithm

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