Vol. 2 No. 4 (2020), Articles
Vol. 2 No. 4 (2020)

Improved Version of Graph-Cut Algorithm for CT Images of Lung Cancer With Clinical Property Condition

Articles
Published 12-12-2020
Samuel Manoharan
Professor, Department of Electronics, Bharathiyar College of Engineering and Technology, Thiruvettakudy, Karaikal, India
A. Sathesh
Department of EEE, Eritrea Institute of Technology, Eritrea
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Keywords

lung cancer
computed tomography
graph cut segmentation

How to Cite

Manoharan, Samuel, and A. Sathesh. 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): 201-6. https://doi.org/10.36548/jaicn.2020.4.002.
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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.

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