An adaptive density-weighted contrast enhancement filter for mammographic breast mass detection
- Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Radiology
- Univ. of Chicago, IL (United States). Dept. of Radiology
This paper presents a novel approach for segmentation of suspicious mass regions in digitized mammograms using a new adaptive density-weighted contrast enhancement (DWCE) filter in conjunction with Laplacian-Gaussian (LG) edge detection. The DWCE enhances structures within the digitized mammogram so that a simple edge detection algorithm can be used to define the boundaries of the objectives. Once the object boundaries are known, morphological features are extracted and used by a classification algorithm to differentiate regions within the image. This paper introduces the DWCE algorithm and presents results of a preliminary study based on 25 digitized mammograms with biopsy proven masses. It also compares morphological feature classification based on sequential thresholding, linear discriminant analysis, and neural network classifiers for reduction of false-positive detections.
- OSTI ID:
- 207909
- Journal Information:
- IEEE Transactions on Medical Imaging, Journal Name: IEEE Transactions on Medical Imaging Journal Issue: 1 Vol. 15; ISSN 0278-0062; ISSN ITMID4
- Country of Publication:
- United States
- Language:
- English
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