{"title":"医学成像的计算方法。","authors":"R Calamai, G Coppini, M Demi, R Poli, G Valli","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Notwithstanding the progress in medical imaging by means of computer-based techniques, several problems still remain unsolved in this field. In particular, a unified approach for the treatment of biological complexity and variability is lacking. Moreover, perceptive and cognitive aspects of medical vision play an important role in a computational approach to medical imaging and must be carefully considered. The recent developments of Computer Vision and Artificial Intelligence suggest that such a computational approach is feasible. As a consequence, symbolic representations of the clinical information contained in the images as well as adequate processing techniques are necessary. In this way the treatment of uncertainty and the qualitative analysis are made possible. Moreover, due to the intrinsic homogeneity of symbolic representations, the comparison of different image sources, signals and clinical data is attainable. In the paper, the basic principles of Computer Vision are summarized and the need of a specific computational theory for medical vision is emphasized. Afterwards, the main characteristics of integrated systems for computational imaging in medicine, are described. Some examples relative to the imaging of the cardiovascular system are also given. Although the development of artificial vision systems in biomedicine is still an area of research, very promising perspectives are opened by a computational approach.</p>","PeriodicalId":76654,"journal":{"name":"The Journal of nuclear medicine and allied sciences","volume":"34 1","pages":"42-50"},"PeriodicalIF":0.0000,"publicationDate":"1990-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A computational approach to medical imaging.\",\"authors\":\"R Calamai, G Coppini, M Demi, R Poli, G Valli\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Notwithstanding the progress in medical imaging by means of computer-based techniques, several problems still remain unsolved in this field. In particular, a unified approach for the treatment of biological complexity and variability is lacking. Moreover, perceptive and cognitive aspects of medical vision play an important role in a computational approach to medical imaging and must be carefully considered. The recent developments of Computer Vision and Artificial Intelligence suggest that such a computational approach is feasible. As a consequence, symbolic representations of the clinical information contained in the images as well as adequate processing techniques are necessary. In this way the treatment of uncertainty and the qualitative analysis are made possible. Moreover, due to the intrinsic homogeneity of symbolic representations, the comparison of different image sources, signals and clinical data is attainable. In the paper, the basic principles of Computer Vision are summarized and the need of a specific computational theory for medical vision is emphasized. Afterwards, the main characteristics of integrated systems for computational imaging in medicine, are described. Some examples relative to the imaging of the cardiovascular system are also given. Although the development of artificial vision systems in biomedicine is still an area of research, very promising perspectives are opened by a computational approach.</p>\",\"PeriodicalId\":76654,\"journal\":{\"name\":\"The Journal of nuclear medicine and allied sciences\",\"volume\":\"34 1\",\"pages\":\"42-50\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of nuclear medicine and allied sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of nuclear medicine and allied sciences","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Notwithstanding the progress in medical imaging by means of computer-based techniques, several problems still remain unsolved in this field. In particular, a unified approach for the treatment of biological complexity and variability is lacking. Moreover, perceptive and cognitive aspects of medical vision play an important role in a computational approach to medical imaging and must be carefully considered. The recent developments of Computer Vision and Artificial Intelligence suggest that such a computational approach is feasible. As a consequence, symbolic representations of the clinical information contained in the images as well as adequate processing techniques are necessary. In this way the treatment of uncertainty and the qualitative analysis are made possible. Moreover, due to the intrinsic homogeneity of symbolic representations, the comparison of different image sources, signals and clinical data is attainable. In the paper, the basic principles of Computer Vision are summarized and the need of a specific computational theory for medical vision is emphasized. Afterwards, the main characteristics of integrated systems for computational imaging in medicine, are described. Some examples relative to the imaging of the cardiovascular system are also given. Although the development of artificial vision systems in biomedicine is still an area of research, very promising perspectives are opened by a computational approach.