{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T19:02:47Z","timestamp":1771614167101,"version":"3.50.1"},"reference-count":15,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,1,8]],"date-time":"2019-01-08T00:00:00Z","timestamp":1546905600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2019,1,8]]},"abstract":"<jats:p>The objective of this paper is to explore an expedient image segmentation algorithm for medical images to curtail the physicians\u2019 interpretation of computer tomography (CT) scan images. Modern medical imaging modalities generate large images that are extremely grim to analyze manually. The consequences of segmentation algorithms rely on the exactitude and convergence time. At this moment, there is a compelling necessity to explore and implement new evolutionary algorithms to solve the problems associated with medical image segmentation. Lung cancer is the frequently diagnosed cancer across the world among men. Early detection of lung cancer navigates towards apposite treatment to save human lives. CT is one of the modest medical imaging methods to diagnose the lung cancer. In the present study, the performance of five optimization algorithms, namely, <jats:italic>k<\/jats:italic>-means clustering, <jats:italic>k<\/jats:italic>-median clustering, particle swarm optimization, inertia-weighted particle swarm optimization, and guaranteed convergence particle swarm optimization (GCPSO), to extract the tumor from the lung image has been implemented and analyzed. The performance of median, adaptive median, and average filters in the preprocessing stage was compared, and it was proved that the adaptive median filter is most suitable for medical CT images. Furthermore, the image contrast is enhanced by using adaptive histogram equalization. The preprocessed image with improved quality is subject to four algorithms. The practical results are verified for 20 sample images of the lung using MATLAB, and it was observed that the GCPSO has the highest accuracy of 95.89%.<\/jats:p>","DOI":"10.1155\/2019\/4909846","type":"journal-article","created":{"date-parts":[[2019,1,8]],"date-time":"2019-01-08T19:01:33Z","timestamp":1546974093000},"page":"1-16","source":"Crossref","is-referenced-by-count":81,"title":["Lung Cancer Detection Using Image Segmentation by means of Various Evolutionary Algorithms"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7798-7363","authenticated-orcid":true,"given":"K.","family":"Senthil Kumar","sequence":"first","affiliation":[{"name":"Assistant Professor, Department of Electrical and Electronics Engineering, University College of Engineering, Arni, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6924-9021","authenticated-orcid":true,"given":"K.","family":"Venkatalakshmi","sequence":"additional","affiliation":[{"name":"Assistant Professor, Department of Electronics and Communication Engineering, University College of Engineering Tindivanam, Tindivanam, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2894-8675","authenticated-orcid":true,"given":"K.","family":"Karthikeyan","sequence":"additional","affiliation":[{"name":"Teaching Fellow, Department of Electronics and Communication Engineering, University College of Engineering, Arni, India"}]}],"member":"311","reference":[{"issue":"4","key":"1","volume":"9","year":"2016","journal-title":"Journal of Chemical and Pharmaceutical Sciences"},{"issue":"5","key":"2","first-page":"16736","volume":"5","year":"2016","journal-title":"International Journal of Engineering and Computer Science"},{"issue":"1","key":"3","volume":"5","year":"2016","journal-title":"International Journal of Scientific Research Engineering and Technology"},{"issue":"1","key":"4","first-page":"175","volume":"4","year":"2015","journal-title":"International Journal of Computer Science and Mobile Computing"},{"issue":"5","key":"5","volume":"1","year":"2011","journal-title":"International Journal of Soft Computing and Engineering"},{"issue":"2","key":"8","first-page":"113","volume":"17","year":"2007","journal-title":"International Journal on Neural and Mass-Parallel Computing and Information Systems"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.3923\/itj.2007.554.560"},{"issue":"5","key":"10","first-page":"4405","volume":"12","year":"2016","journal-title":"Global Journal of Pure and Applied Mathematics"},{"key":"11","first-page":"444","volume":"10","year":"2015","journal-title":"International Journal of Applied Engineering Research"},{"issue":"4","key":"13","first-page":"327","volume":"5","year":"2008","journal-title":"International Arab Journal of Information Technology"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.5120\/12751-9694"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.5194\/isprsannals-i-7-341-2012"},{"issue":"1","key":"17","first-page":"17","volume":"1","year":"2013","journal-title":"International Journal of Science and Technology"},{"issue":"6","key":"18","first-page":"351","volume":"8","year":"2016","journal-title":"Journal of Chemical and Pharmaceutical Research"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.mspro.2015.06.077"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2019\/4909846.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2019\/4909846.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2019\/4909846.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,1,8]],"date-time":"2019-01-08T19:01:40Z","timestamp":1546974100000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cmmm\/2019\/4909846\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,8]]},"references-count":15,"alternative-id":["4909846","4909846"],"URL":"https:\/\/doi.org\/10.1155\/2019\/4909846","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"value":"1748-670X","type":"print"},{"value":"1748-6718","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,8]]}}}