2 research outputs found
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Evaluation of a Multi-Scale Enhancement Protocol for Digital Mammography
We have carried out a receiver operating characteristics (ROC) study for the enhancement of mammographic features in digitized mammograms. The study evaluated the benefits of multi-scale enhancement methods in terms of diagnostic performance of radiologists. The enhancement protocol relied on multi-scale expansions and non-linear enhancement functions. Dyadic spline wavelet functions (first derivative of a cubic spline) were used together with a sigmoidal non-linear enhancement function. We designed a computer interface on a softcopy display and performed an ROC study with three radiologists, who specialized in mammography. Clinical cases were obtained from a national mammography database of digitized radiographs prepared by the University of South Florida (USF) and Harvard Medical School. Our study focused on dense mammograms, i.e. mammograms of density 3 and 4 on the American College of Radiology (ACR) breast density rating, which are the most difficult cases in screening, were selected. To compare the performance of radiologists with and without using multi-scale enhancement, two groups of 30 cases each were diagnosed. Each group contained 15 cases of cancerous and 15 cases of normal mammograms. Conventional ROC analysis was applied, and the resulting ROC curves indicated improved diagnostic performance when radiologists used multi-scale non-linear enhancement
X-ray Image Segmentation and An Internet-based Tool for Medical Validation
Segmentation of vertebrae in X-ray images is a difficult task that requires an effective segmentation procedure. Noise, poor image contrast, occlusions and shape variability are some of the challenges in many of the spine X-ray images archived at the U.S. National Library of Medicine (NLM). In this thesis, we propose a curvature-based corner matching approach, which exploits the posterior corners of the vertebra to estimate the location and orientation of the vertebrae. The key advantage of the proposed approach is execution time, roughly about one-fifth of the previous approach that uses the generalized Hough transform when tested on a sizeable set of cervical spine images.
This thesis also presents the first ever effort to develop a prototype internet-based medical image segmentation and pathology validation tool, which enables radiologists to validate computer generated image segmentations, modify existing or create new segmentation in addition to identifying pertinent pathology data