Applications of decision trees to filtering and segmentation of breast cancer fine needle biopsy microscope images

• Autorzy: Nieczkowski T. , Obuchowicz A.
• Języki publikacji: EN

Abstrakty

EN

This paper provides a description of application of the regular decision tree at the pre-segmentation stage of the breast cancer fine needle biopsy microscope image analysis. The purpose the application is to improve results of segmentation, which is the next stage of the process. The proposed approach consists in the classification of image pixels based on their colour. The result is the image with pixels colour representing the probability of association to one of three classes: the nucleus, the intemucleus matter and the background. The enhancement is evaluated by applying the thresholding segmentation to the resultant image and comparing it with the results of the application of the similar process without the pre-segmentation stage.

Słowa kluczowe

EN

image segmentation; image processing; decision tree; classification; cytology; biopsy

PL

segmentacja obrazów; przetwarzanie obrazu; drzewo decyzyjne; klasyfikacja; cytologia; biopsja

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2007
• Tom: Vol. 27, no. 4
• Strony: 59--70
• Opis fizyczny: Bibliogr. 6 poz., rys., wykr.

Twórcy

autor

Nieczkowski T.

autor

Obuchowicz A.

• Institute of Control and Computation Engineering, Faculty of Electrical Engineering, Computer Science and Telecommunications, University of Zielona Góra, Podgórna 50, 65-245 Zielona Góra, Poland,

Bibliografia

• 1. Marciniak A., Monczak R., Kołodziński M., Prętki P., Obuchowicz A.: Fine Needle Biopsy Breast Cancer Diagnostic Benchmark (in Polish), SIIB 2004, Wyd. PreTEXT, Kraków 2004.
• 2. Kurzyński M.: Objects recognition - statistical methods (in Polish), Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 1997.
• 3. Zieliński K.W., Strzelecki M.: Computer Analysis of Biomedical Image. Preface to quantitive morphometry and pathology (in Polish), Wydawnictwo Naukowe PWN, Warszawa - Łódź 2002.
• 4. Kantardzi M.: Data Mining. Concepts, Models, Methods, and Algorithms, Wiley-IEEE Press, 2002.
• 5. Zhang Y. J.: A survey on evaluation methods for image segmentation, Pattern Recognition, Elsevier Science Ltd, 1996, 29, 8, 1335-1346.
• 6. http://rsb.info.nih.gov/nih-image/about.html, page US National Institutes of Health (NIH).