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Content-based image retrieval (CBIR) shows great significance in clinical decision-making, which explores the visual content of medical images rather than keywords, tags, or descriptions. It provides doctors an image-guided approach to explore relevant cases that could offer doctors instructive reference. Mammogram screening has been known to be widely used in the early stage diagnosis of breast cancer...
A novel word-based algorithm is presented to detect duplicate Picture in Picture (PiP) video sequences in this study. The conventional edge-based methods used to extract the PiP regions are not robust in the noise and blurring images. Bag of Words (BOW) model emphasizes words ambiguity and ignores spatial information. Without detecting the PiP regions and unlike the traditional word based approach,...
In this work, we described a new two-stage hierarchical framework for mammogram retrieval. We tested the proposed approach on the reference library from USF-DDSM. For each query ROI (region of interest), the proposed scheme first computes its 14 texture and shape features, then the voting method based on five classifiers is used to classify the ROIs in the reference library, this phase eliminates...
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