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Tree structured wavelet transform segmentation of microcalcifications in digital mammography
Author(s) -
Qian Wei,
Kallergi Maria,
Clarke Laurence P.,
Li HuaiDong,
Venugopal Priya,
Song Dansheng,
Clark Robert A.
Publication year - 1995
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.597562
Subject(s) - microcalcification , artificial intelligence , computer science , computer vision , segmentation , digital mammography , wavelet , mammography , pattern recognition (psychology) , wavelet transform , image segmentation , medicine , cancer , breast cancer
A novel multistage algorithm is proposed for the automatic segmentation of microcalcification clusters (MCCs) in digital mammography. First, a previously reported tree structured nonlinear filter is proposed for suppressing image noise, while preserving image details, to potentially reduce the false positive (FP) detection rate for MCCs. Second, a tree structured wavelet transform (TSWT) is applied to the images for microcalcification segmentation. The TSWT employs quadrature mirror filters as basic subunits for both multiresolution decomposition and reconstruction processes, where selective reconstruction of subimages is used to segment MCCs. Third, automatic linear scaling is then used to display the image of the segmented MCCs on a computer monitor for interpretation. The proposed algorithms were applied to an image database of 100 single view mammograms at a resolution of 105 μm and 12 bits deep (4096 gray levels). The database contained 50 cases of biopsy proven malignant MCCs, 8 benign cases, and 42 normal cases. The measured sensitivity (true positive detection rate) was 94% with a low FP detection rate of 1.6 MCCs/image. The image details of the segmented MCCs were reasonably well preserved, for microcalcification of less than 500 μm, with good delineation of the extent of the microcalcification clusters for each case based on visual criteria.