Title :
Lesion detection and characterization in digital mammography by Bezier histograms
Author :
Qi, Hairong ; Snyder, Wesley E.
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fDate :
29 Oct-1 Nov 1998
Abstract :
Due to some important properties of Bezier splines, they have great potential use in computer-aided mammogram diagnosis. In this paper, Bezier splines are applied in both lesion detection and characterization processes, where lesion detection is achieved by segmentation using a natural threshold computed from Bezier smoothed histogram; and lesion characterization is achieved by measuring the fitness between Gaussian and Bezier histograms of data projected on principal components. Experimental results show that this approach is efficient, easy to use, and can achieve high sensitivity
Keywords :
image classification; image segmentation; image texture; mammography; medical image processing; principal component analysis; splines (mathematics); tumours; Bezier histograms; Bezier splines; Gaussian histograms; computer-aided mammogram diagnosis; digital mammography; high sensitivity; histogram matching; lesion characterization; lesion detection; natural threshold; principal components; region growing; segmentation; shape information; smoothed histogram; Computer errors; Histograms; Human factors; Image segmentation; Lesions; Mammography; Markov random fields; Shape; Stochastic processes; Wavelet analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.745623
