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Bone Suppression in Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined with Total Variation Minimization Smoothing and Consistency Processing
[chapter]
2013
Computational Intelligence in Biomedical Imaging
Our purpose was to separate bony structures such as ribs and clavicles from soft tissue in chest radiographs (CXRs). Although massive-training artificial neural networks (MTANNs) have been developed for suppression of ribs, they did not suppress rib edges, ribs close to the lung wall, and the clavicles well. To address this issue, we developed anatomically specific multiple MTANNs that are designed to suppress bones in different anatomic segments in the lungs. Each of 8 anatomically specific
doi:10.1007/978-1-4614-7245-2_9
fatcat:mv6yccevtbatrhq32zkuvkmh5y