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Home / Archives / Volume-2 / Issue-4 / Article-2

Volume - 2 | Issue - 4 | december 2020

Improved Version of Graph-Cut Algorithm for CT Images of Lung Cancer With Clinical Property Condition
Dr. Samuel Manoharan, A. Sathesh  278  169
Pages: 201-206
Cite this article
Manoharan, D. S. & Sathesh, A. (2020). Improved Version of Graph-Cut Algorithm for CT Images of Lung Cancer With Clinical Property Condition. Journal of Artificial Intelligence and Capsule Networks, 2(4), 201-206. doi:10.36548/jaicn.2020.4.002
Published
12 December, 2020
Abstract

In a clinical evaluation, the detection of lung cancer is a challenging task. Segmentation methods are used to detect the extra growing nodule. Early diagnosis of lung cancer is significant in clinical research. The early stage of lung nodules is very soft tissues and tough to segment accurately. Generally, conservative graph cut methods are very weak to detect those soft edges in medical images. In this article, the proposed algorithm is improved to obtain the accuracy of the process to segment the edges than the conventional graph cut methods. This investigation is executed to shows the accuracy of lung segmentation.

Keywords

lung cancer computed tomography graph cut segmentation

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