Optimized Image Extracting Algorithm from Original Image using Ground Truth

Information technology has been playing major roles in the field of medical research and analysis in diagnosing as well as treatment of diseases. Colon cancer is among one of the diseases to be identified effectively and accurately. The scarcity of datasets however hinders the progress of researcher...

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Bibliographic Details
Published inProceedings (International Conference on ICT for Smart Society. Online) Vol. 7; pp. 1 - 5
Main Authors Isidro, Ariel, Fajardo, Arnel
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2019
Subjects
Colon cancer
Colorectal cancer
Convolutional neural networks
Deep learning
Diseases
Ground Truth
Information technology
Medical diagnostic imaging
Python
Python programming language
string slicing
Online AccessGet full text
ISSN2640-0545
DOI10.1109/ICISS48059.2019.8969816

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Summary:Information technology has been playing major roles in the field of medical research and analysis in diagnosing as well as treatment of diseases. Colon cancer is among one of the diseases to be identified effectively and accurately. The scarcity of datasets however hinders the progress of researchers. This paper introduces an algorithm that extracts image from an original image using a ground truth. The algorithm used Python programming language in string slicing. The algorithm was able to extract both polyp and non-polyp images and decreases 8% of the time it takes than original image. Furthermore, this algorithm is useful in creating future studies.
ISSN:2640-0545
DOI:10.1109/ICISS48059.2019.8969816