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Morphology-based algorithm and application for mammographic masses segmentation
Author(s)
Date Issued
January 1, 2013
Type
Conference Paper
Abstract
Medical images segmentation is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, segmentation is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image segmentation. In this paper, basic morphological theory and operations are introduced at first, and then a novel morphological segmentation algorithm is proposed to detect the segment of mammographic masses with salt-And-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and segmentation than the usually used template-based segmentation algorithms and general morphological segmentation algorithms. Furthermore, the application is helpful for physician and doctors in diagnosis of the breast cancer in further steps.
Citation
Proceedings of the SICE Annual Conference, 837-840, 2013