Tytuł artykułu
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Wybrane pełne teksty z tego czasopisma
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Języki publikacji
Abstrakty
Currently used diagnostic procedures for identification of the prostate cancer (PCa) are insufficient. It occurs quite often that the existing PCa cannot be detected. Therefore scientists search for other methods enabling a better efficacy of diagnosis. The perfusion computed tomography technique (p-CT), which measures some parameters of blood flow within diagnosed organs, is supposed to avoid such problems, even in particularly hard cases. In this paper some methods of automatic analysis of prostate perfusion tomographic images are presented and discussed. Although the work concentrates only on one image derived from one patient, we can see the complexity and importance of the task. The proposed algorithms and methods based on the Haralick's co-occurrence matrices seems to be the appropriate technique to point out the cancerous lesions. In the further work described algorithms will be tested on a large set of patients. This goal needs close cooperation between radiologists, pathologist, computer scientists and engineers. The final goal is to develop a professional diagnostic system used in computer aided prostate diagnosis.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
25--30
Opis fizyczny
Bibliogr. 8 poz., rys., tab., zdj.
Twórcy
autor
- Institute of Computer Science Jagiellonian University, ul. Łojasiewicza 6, 30-438 Kraków
autor
- Department of Automatics AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
Bibliografia
- 1. Estimated New Cancer Cases and Deaths by Sex, US, 2008,http://www.cancer.org/docroot/MED/content/downloads/MED_1_1x_CFF2008_Estimate-d_Cancer_Cases_Deaths_AH.asp
- 2. Krajowy Rejestr Nowotworów, Raporty na podstawie danych Centrum Onkologii, http://85.128.14.124/krn
- 3. Hricak H., Choyke P., Eberhardt S. et al., Imaging Prostate Cancer. A Multidisciplinary Perspective, Radiology 2007; 243(1): 28-53.
- 4. Roscigno M., Scattoni V., Bertini R. et al., Diagnosis of prostate cancer. State of the art, Minerva Urol Nefrol 2004; 56(2): 123-145.
- 5. Simon H. (ed.), Prostate Cancer, [in:] Lifespan's A - Z Health Information Library 2006, http://www.lifespan.org/adam/indepthreports/10/000033.html
- 6. Miles K. A., Functional computed tomography in oncology, European Journal of Cancer 2002; 38:2079-2084.
- 7. Haralick R. M., Shanmugam K., Dinstein I., Textural features for image classification, IEEE Transactions on Systems, Man and Cybernetics 1973; 3:610-621.
- 8. Walker R. F., Adaptive multi-scale texture analysis with application to automated cytology, University of Queensland 1997.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-05f5b193-b435-4204-b8dd-b358a7f3c1eb