Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix

Title

Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix

Creator

Dominic D.; Balachandran K.

Description

Early detection of any sort of cancer, particularly lung cancer, which is one of the worlds most lethal illnesses, can save many lives. Life expectancy can be improved and the degree of mortality reduced by adopting the early forecast. While there are different methods like X-ray and CT scans to detect lung cancer cells, CT images resulted as more favored. The 2D images are used for more accurate medical results, such as CT scans. The proposed approach here will address how to interpret the CT images for the Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix. This research will explore how the image conversion can be achieved through different methods of image processing to obtain better results from CT images. The Confusion Matrix helps to estimate inequality in a picture pattern. After the evaluation of the processed images by Confusion Matrix, a final accuracy with a result of 93% is obtained. 2023 Scrivener Publishing LLC.

Source

Data Engineering and Data Science: Concepts and Applications, pp. 317-333.

Date

2023-01-01

Publisher

wiley

Subject

Computer tomography (CT); LBP features; preprocessing; processing; smoothening

Coverage

Dominic D., School of Computer Science and Engineering, Christ (Deemed to be University), Bengaluru, India; Balachandran K., School of Computer Science and Engineering, Christ (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 978-111984199-9; 978-111984187-6

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1002/9781119841999.ch13

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174117232&doi=10.1002%2f9781119841999.ch13&partnerID=40&md5=2eb43c0745c7d7a34892f39529afac72