Method of automatic detection of tumors in mammogram

Mei Xie; Zheng Ma

doi:10.1117/12.440290

18 September 2001 Method of automatic detection of tumors in mammogram

Mei Xie, Zheng Ma

Proceedings Volume 4556, Data Mining and Applications; (2001) https://doi.org/10.1117/12.440290
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

Prevention and early diagnosis of tumors in mammogram are foremost. Unfortunately, these images are often corrupted by the noise due to the film noise and the background texture of the images, which did not allow isolation of the target information from the background noise, and often results in the suspicious area to be analyzed inaccurately. In order to achieve more accurate detection and segmentation tumors, the quality of the images need to improve, (including to suppressing noise and enhancing the contrast of the image). This paper presents a new adaptive histogram threshold method approach for segmentation of suspicious mass regions in digitized images. The method use multi-scale wavelet decomposition and a threshold selection criterion based on a transformed image¡¯s histogram. This separation can help eliminate background noise and discriminates against objects of different size and shape. The tumors are extracted by used an adaptively bayesian classifier. We demonstrate that the method proposed can greatly improve the accuracy of detection in tumors.

Citation Download Citation

Mei Xie and Zheng Ma "Method of automatic detection of tumors in mammogram", Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); https://doi.org/10.1117/12.440290

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