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

Jacek Śmietański; Ryszard Tadeusiewicz; Elżbieta Łuczyńska

International Journal of Applied Mathematics and Computer Science (2010)

  • Volume: 20, Issue: 1, page 149-156
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Jacek Śmietański, Ryszard Tadeusiewicz, and Elżbieta Łuczyńska. "Texture analysis in perfusion images of prostate cancer - A case study." International Journal of Applied Mathematics and Computer Science 20.1 (2010): 149-156. <http://eudml.org/doc/207970>.

@article{JacekŚmietański2010,
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.},
author = {Jacek Śmietański, Ryszard Tadeusiewicz, Elżbieta Łuczyńska},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {prostate cancer; perfusion computed tomography; medical image analysis; pattern recognition},
language = {eng},
number = {1},
pages = {149-156},
title = {Texture analysis in perfusion images of prostate cancer - A case study},
url = {http://eudml.org/doc/207970},
volume = {20},
year = {2010},
}

TY - JOUR
AU - Jacek Śmietański
AU - Ryszard Tadeusiewicz
AU - Elżbieta Łuczyńska
TI - Texture analysis in perfusion images of prostate cancer - A case study
JO - International Journal of Applied Mathematics and Computer Science
PY - 2010
VL - 20
IS - 1
SP - 149
EP - 156
AB - 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.
LA - eng
KW - prostate cancer; perfusion computed tomography; medical image analysis; pattern recognition
UR - http://eudml.org/doc/207970
ER -

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