<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>The analysis of prostate images is one of the most complex tasks in medical images interpretation. It is sometimes very difficult to detect early prostate cancer using currently available diagnostic methods. But the examination based on perfusion computed tomography (p-CT) may avoid such problems even in particularly difficult cases. However, the lack of computational methods useful in the interpretation of perfusion prostate images makes it unreliable because the diagnosis depends mainly on the doctor's individual opinion and experience. In this paper some methods of automatic analysis of prostate perfusion tomographic images are presented and discussed. Some of the presented methods are adopted from papers of other researchers, and some are elaborated by the authors. This presentation of the method and algorithms is important, but it is not the master scope of the paper. The main purpose of this study is computational (deterministic and independent) verification of the usefulness of the p-CT technique in a specific case. It shows that it is possible to find computationally attainable properties of p-CT images which allow pointing out the cancerous lesion and can be used in computer aided medical diagnosis.</p></abstract>

The analysis of prostate images is one of the most complex tasks in medical images interpretation. It is sometimes very difficult to detect early prostate cancer using currently available diagnostic methods. But the examination based on perfusion computed tomography (p-CT) may avoid such problems even in particularly difficult cases. However, the lack of computational methods useful in the interpretation of perfusion prostate images makes it unreliable because the diagnosis depends mainly on the doctor's individual opinion and experience. In this paper some methods of automatic analysis of prostate perfusion tomographic images are presented and discussed. Some of the presented methods are adopted from papers of other researchers, and some are elaborated by the authors. This presentation of the method and algorithms is important, but it is not the master scope of the paper. The main purpose of this study is computational (deterministic and independent) verification of the usefulness of the p-CT technique in a specific case. It shows that it is possible to find computationally attainable properties of p-CT images which allow pointing out the cancerous lesion and can be used in computer aided medical diagnosis.

Texture analysis in perfusion images of prostate cancer—A case study

Institute of Computer Science, Jagiellonian University, ul. Łojasiewicza 6, 30-438 Cracow, Poland

Department of Automatics, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland

Department of Diagnostic Radiology, Centre of Oncology, ul. Garncarska 11, 31-115 Cracow, Poland

International Journal of Applied Mathematics and Computer Science

{"article-title":"Texture analysis in perfusion images of prostate cancer\u2014A case study"}

The analysis of prostate images is one of the most complex tasks in medical images interpretation. It is sometimes very difficult to detect early prostate...

Texture analysis in perfusion images of prostate cancer—A case study

Published Online: Mar 25, 2010

Page range: 149 - 156

DOI: https://doi.org/10.2478/v10006-010-0011-9

Keywords
prostate cancer, perfusion computed tomography, medical image analysis, pattern recognition

This content is open access.

Texture analysis in perfusion images of prostate cancer—A case study

Published Online: Mar 25, 2010

Page range: 149 - 156

DOI: https://doi.org/10.2478/v10006-010-0011-9

Keywordsprostate cancer, perfusion computed tomography, medical image analysis, pattern recognition

This content is open access.

Keywords
prostate cancer, perfusion computed tomography, medical image analysis, pattern recognition