1 July 1991 Development of a neural network for early detection of renal osteodystrophy
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Abstract
Bone erosion presenting as subperiosteal resorption on the phalanges of the hand is an early manifestation of hyperparathyroidism associated with chronic renal failure. At present, the diagnosis is made by trained radiologists through visual inspection of hand radiographs. In this study, a neural network is being developed to assess the feasibility of computer-aided detection of these changes. A two-pass approach is adopted. The digitized image is first compressed by a Laplacian pyramid compact code. The first neural network locates the region of interest using vertical projections along the phalanges and then the horizontal projections across the phalanges. A second neural network is used to classify texture variations of trabecular patterns in the region using a concurrence matrix as the input to a two-dimensional sensor layer to detect the degree of associated osteopenia. Preliminary results demonstrate the feasibility of this approach.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shirley Nian-Chang Cheng, Shirley Nian-Chang Cheng, Heang-Ping Chan, Heang-Ping Chan, Ronald Adler, Ronald Adler, Loren T. Niklason, Loren T. Niklason, Chair-Li Chang, Chair-Li Chang, "Development of a neural network for early detection of renal osteodystrophy", Proc. SPIE 1450, Biomedical Image Processing II, (1 July 1991); doi: 10.1117/12.44288; https://doi.org/10.1117/12.44288
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