{"title":"基于ImageJ的对比度分布方法对脑卒中患者医学影像的分析","authors":"Budiani Destyningtias, A. Nugroho, S. Heranurweni","doi":"10.26623/ELEKTRIKA.V10I1.1130","DOIUrl":null,"url":null,"abstract":"This study aims to develop medical image processing technology, especially medical images of CT scans of stroke patients. Doctors in determining the severity of stroke patients usually use medical images of CT scans and have difficulty interpreting the extent of bleeding. Solutions are used with contrast stretching which will distinguish cell tissue, skull bone and type of bleeding. This study uses contrast stretching from the results of CT Scan images produced by first turning the DICOM Image into a JPEG image using the help of the ImageJ program. The results showed that the histogram equalization method and statistical texture analysis could be used to distinguish normal MRI and abnormal MRI detected by stroke.Keywords : Stroke, MRI, Dicom, JPEG, ImageJ, Contrast Stretching ","PeriodicalId":31998,"journal":{"name":"Elektrika","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analisa Citra Medis Pada Pasien Stroke dengan Metoda Peregangan Kontras Berbasis ImageJ\",\"authors\":\"Budiani Destyningtias, A. Nugroho, S. Heranurweni\",\"doi\":\"10.26623/ELEKTRIKA.V10I1.1130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to develop medical image processing technology, especially medical images of CT scans of stroke patients. Doctors in determining the severity of stroke patients usually use medical images of CT scans and have difficulty interpreting the extent of bleeding. Solutions are used with contrast stretching which will distinguish cell tissue, skull bone and type of bleeding. This study uses contrast stretching from the results of CT Scan images produced by first turning the DICOM Image into a JPEG image using the help of the ImageJ program. The results showed that the histogram equalization method and statistical texture analysis could be used to distinguish normal MRI and abnormal MRI detected by stroke.Keywords : Stroke, MRI, Dicom, JPEG, ImageJ, Contrast Stretching \",\"PeriodicalId\":31998,\"journal\":{\"name\":\"Elektrika\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Elektrika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26623/ELEKTRIKA.V10I1.1130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Elektrika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26623/ELEKTRIKA.V10I1.1130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analisa Citra Medis Pada Pasien Stroke dengan Metoda Peregangan Kontras Berbasis ImageJ
This study aims to develop medical image processing technology, especially medical images of CT scans of stroke patients. Doctors in determining the severity of stroke patients usually use medical images of CT scans and have difficulty interpreting the extent of bleeding. Solutions are used with contrast stretching which will distinguish cell tissue, skull bone and type of bleeding. This study uses contrast stretching from the results of CT Scan images produced by first turning the DICOM Image into a JPEG image using the help of the ImageJ program. The results showed that the histogram equalization method and statistical texture analysis could be used to distinguish normal MRI and abnormal MRI detected by stroke.Keywords : Stroke, MRI, Dicom, JPEG, ImageJ, Contrast Stretching