Detection and Segmentation of Medical Images Using Generic Algorithms

• Published in: International journal of extreme automation and connectivity in healthcare Vol. 3; no. 1; pp. 39 - 46
• Main Authors: Bhatt, Chintan M, Khandhar, Hardev Mukeshbhai, Fong, Simon
• Format: Journal Article
• Language: English
• Published: Hengqin Island IGI Global 01.01.2021
• Subjects: Algorithms; Astronomy; Computed tomography; CT imaging; Diagnostic imaging; Digital imaging; Disaster management; Edge detection; Genetic algorithms; Geographic information systems; Image processing; Image segmentation; Medical imaging; Medical imaging equipment; Object recognition
• ISSN: 2577-4794; 2577-4808
• DOI: 10.4018/IJEACH.2021010104

Image processing plays an indispensable and significant role in the development of various fields like medical imaging, astronomy, GIS, disaster management, agriculture monitoring, and so on. Medical images which are recorded in digital forms are processed by high-end computers to extract whatever information we desire. In the fast-developing modern world of medical imaging diagnosis and prognosis, where manual photo interpretation is time-consuming, automatic object detection from devices like CT-Scans and MRIs has limited potential to generate the required results. This article addresses the process of identifying Region of Interests in cancer based medical images based on combination of Otsu’s algorithm and Canny edge detection methods. The primary objective of this paper is to derive meaningful and potential information from medical image in different scenarios by applying the image segementation in combination with genetic algorithms in a robust manner to detect region of interest.