Comparison of thresholding methods for breast tumor cell segmentation

Autor:	Hye-Jin Jeong, Hae-Gil Hwang, Tae-Yoon Kim, Hyun-Ju Choi, Hyung-Seon Park, Heung-Kook Choi
Rok vydání:	2005
Předmět:	medicine.diagnostic_test Iterative method business.industry Image segmentation medicine.disease Thresholding Otsu's method symbols.namesake Breast cancer medicine symbols Mammography Preprocessor Segmentation Computer vision Artificial intelligence skin and connective tissue diseases business
Zdroj:	Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005..
DOI:	10.1109/health.2005.1500489
Popis:	Breast cancer was the most commonly occurring malignancy among women, so study of breast cancer are important. This paper is preprocessing of breast tumor research for segmentation method. There are many thresholding methods. Many thresholding methods developed but they have different result in each image. So we need automatic thresholding method because manual operating is tedious, time-consuming. This study compared result of 6 automatic thresholding method and 1 semi-supervised thresholding method in breast tumor image. Otsu's method and Iterative selection are good result in breast tumor cell images. So we expected results using Otsu's method and Iterative Selection to help for determining and diagnosing the breast tumor.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d244d4f37d1705f823fb041366f5d439 https://doi.org/10.1109/health.2005.1500489 Zobrazit plný text záznamu