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• W2069701095 abstract "Rationale and Objectives A method for the automatic detection and the visualization of erosions caused by rheumatoid arthritis is investigated. Erosion-enhanced viewing is a contribution to the computer-aided diagnosis of rheumatoid arthritis. It supports the clinician by providing the automatic marking of erosions and the visualization of any deviations from intact anatomy for a concise reviewing interface. Materials and Methods A generative appearance model is used to capture the variability of intact bone and erosions. The algorithm marks erosions on hand radiographs using this model, and visualizes these erosions with the help of the residual appearance error after fitting the model built from intact bone texture. The algorithm was evaluated on 17 hand radiographs. The standard of reference was an annotation of the erosions by a musculoskeletal radiologist. Results Detection results from the algorithm are reported for a set of 17 radiographs of moderately diseased hands. With a specificity of 84%, the detection of unequivocal erosions achieved a sensitivity of 85%. A receiver operating characteristic analysis yields an area under the curve of 0.92. The visualization provided a clear representation of the erosions as determined by two musculoskeletal radiologists. Conclusion The automatic spotting of erosions provides promising results, and the visualization of the deviation from healthy anatomy aids clinicians in the evaluation of the erosions and in the reviewing of automatic detection results. A method for the automatic detection and the visualization of erosions caused by rheumatoid arthritis is investigated. Erosion-enhanced viewing is a contribution to the computer-aided diagnosis of rheumatoid arthritis. It supports the clinician by providing the automatic marking of erosions and the visualization of any deviations from intact anatomy for a concise reviewing interface. A generative appearance model is used to capture the variability of intact bone and erosions. The algorithm marks erosions on hand radiographs using this model, and visualizes these erosions with the help of the residual appearance error after fitting the model built from intact bone texture. The algorithm was evaluated on 17 hand radiographs. The standard of reference was an annotation of the erosions by a musculoskeletal radiologist. Detection results from the algorithm are reported for a set of 17 radiographs of moderately diseased hands. With a specificity of 84%, the detection of unequivocal erosions achieved a sensitivity of 85%. A receiver operating characteristic analysis yields an area under the curve of 0.92. The visualization provided a clear representation of the erosions as determined by two musculoskeletal radiologists. The automatic spotting of erosions provides promising results, and the visualization of the deviation from healthy anatomy aids clinicians in the evaluation of the erosions and in the reviewing of automatic detection results." @default.
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• W2069701095 date "2007-10-01" @default.
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• W2069701095 title "Model-Based Erosion Spotting and Visualization in Rheumatoid Arthritis" @default.
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• W2069701095 doi "https://doi.org/10.1016/j.acra.2007.06.013" @default.
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