K. Khongsomboon, P. Indarack, K. Hamamoto, S. Kondo
{"title":"Automatic Parameter Setting for Differential Volume Rendering","authors":"K. Khongsomboon, P. Indarack, K. Hamamoto, S. Kondo","doi":"10.1109/ISCIT.2008.4700175","DOIUrl":null,"url":null,"abstract":"X-ray medical examination technique is indispensable and widely applied. Regarding computerized tomography techniques, several researchers have developed 3D reconstruction from X-ray images. Authors also have already proposed a 3D reconstruction technique from X-ray photograph to present bone structure. However, the technique uses many X-ray photographs. Therefore, there arises X-ray exposure problem. One of the solution is to use X-ray fluoroscopy instead of X-ray photograph. X-ray fluoroscopy uses weak intensity X-ray compared with conventional X-ray photograph. Although fluoroscopy can take movie around object and many view images can be taken, the contrast of image is quite low. To reconstruct 3D image from X-ray fluoroscopy, authors have already proposed a 3D reconstruction from X-ray fluoroscopy for clinical veterinary medicine using differential volume rendering. The volume rendering image can display some organs or tissues by user's manual parameter setting. However, this parameter setting is very difficult and complicated to find the optimal parameters for setting opacity. This paper proposes a method to generate the parameters automatically. The parameters are base differential value and maximum differential value. These parameters are set from first maximum point and second maximum point at differentiated value histogram information. In addition, a possibility can be shown where organs are separated by selection of peak points at the histogram. This paper shows the results of experimental investigation of small dog.","PeriodicalId":215340,"journal":{"name":"2008 International Symposium on Communications and Information Technologies","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Symposium on Communications and Information Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCIT.2008.4700175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
X-ray medical examination technique is indispensable and widely applied. Regarding computerized tomography techniques, several researchers have developed 3D reconstruction from X-ray images. Authors also have already proposed a 3D reconstruction technique from X-ray photograph to present bone structure. However, the technique uses many X-ray photographs. Therefore, there arises X-ray exposure problem. One of the solution is to use X-ray fluoroscopy instead of X-ray photograph. X-ray fluoroscopy uses weak intensity X-ray compared with conventional X-ray photograph. Although fluoroscopy can take movie around object and many view images can be taken, the contrast of image is quite low. To reconstruct 3D image from X-ray fluoroscopy, authors have already proposed a 3D reconstruction from X-ray fluoroscopy for clinical veterinary medicine using differential volume rendering. The volume rendering image can display some organs or tissues by user's manual parameter setting. However, this parameter setting is very difficult and complicated to find the optimal parameters for setting opacity. This paper proposes a method to generate the parameters automatically. The parameters are base differential value and maximum differential value. These parameters are set from first maximum point and second maximum point at differentiated value histogram information. In addition, a possibility can be shown where organs are separated by selection of peak points at the histogram. This paper shows the results of experimental investigation of small dog.