F. Shaik, M. N. Giri Prasad, J. Rao, B. Abdul Rahim, A. Somasekhar
{"title":"Medical image analysis of electron micrographs in diabetic patients using contrast enhancement","authors":"F. Shaik, M. N. Giri Prasad, J. Rao, B. Abdul Rahim, A. Somasekhar","doi":"10.1109/ICMET.2010.5598408","DOIUrl":null,"url":null,"abstract":"Today, there is almost no area of technical endeavor that is not impacted in some way or the other by digital image processing. The principle objective of enhancement is to process an image so that the result is more suitable than original image for specific application. When an image is processed for visual interpretation, the viewer is the ultimate judge of how well a particular method works. Histograms, basis for numerical spatial domain processing techniques provides useful image statistics. These are simple to calculate in software and also lend themselves to economic hardware implementations, thus making them a popular tool for real-time image processing. The transformation or mapping of each pixel of input image into a corresponding pixel of the processed output image is called as “Histogram Equalization”. It is “automatic”, the process which is based on information that can be extracted directly from given image, without the need for further parameter specifications. Diabetes mellitus is a metabolic disorder that characterized by inability of the pancreas to control blood glucose concentration. 80% of deaths in Diabetic patients are due to heart diseases. The main objective of this paper is to observe enhancement of Electron micrograph image of a myocardial capillary from a diabetic patient, and to get image information, pixel regions, Contrast Limited Adaptive Histogram Equalization (CLAHE) and intensity adjustment which mainly helps to educate the diabetic patients to prevent cardiac complications i.e., Diabetic Cardiomyopathy using MATLAB.","PeriodicalId":415118,"journal":{"name":"2010 International Conference on Mechanical and Electrical Technology","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Mechanical and Electrical Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMET.2010.5598408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Today, there is almost no area of technical endeavor that is not impacted in some way or the other by digital image processing. The principle objective of enhancement is to process an image so that the result is more suitable than original image for specific application. When an image is processed for visual interpretation, the viewer is the ultimate judge of how well a particular method works. Histograms, basis for numerical spatial domain processing techniques provides useful image statistics. These are simple to calculate in software and also lend themselves to economic hardware implementations, thus making them a popular tool for real-time image processing. The transformation or mapping of each pixel of input image into a corresponding pixel of the processed output image is called as “Histogram Equalization”. It is “automatic”, the process which is based on information that can be extracted directly from given image, without the need for further parameter specifications. Diabetes mellitus is a metabolic disorder that characterized by inability of the pancreas to control blood glucose concentration. 80% of deaths in Diabetic patients are due to heart diseases. The main objective of this paper is to observe enhancement of Electron micrograph image of a myocardial capillary from a diabetic patient, and to get image information, pixel regions, Contrast Limited Adaptive Histogram Equalization (CLAHE) and intensity adjustment which mainly helps to educate the diabetic patients to prevent cardiac complications i.e., Diabetic Cardiomyopathy using MATLAB.