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• W2016153757 abstract "Bone Age (BA) determination using radiological images of left hands and wrists is important in pediatric endocrinology to correctly assess growth and pubertal maturation. In this paper, we propose a fully automated Greulich and Pyle Atlas (GP) bone age determination system using feature extraction and machine learning classifiers. The original contributions of this paper are as follows: (i) We use commercially available morphing tools to create a modified GP atlas that has images regularly spaced at three month intervals, (ii) We propose a novel Singular Value Decomposition (SVD) based feature extractor to create a feature vector. We use the Scale Invariant Feature Transform (SIFT) to extract features from the images then apply SVD to compose the feature vectors. Then, we train a Neural Network classifier using the generated feature vectors. Our preliminary results show that, even with a small number of training data sets, we obtain promising results. Future direction is discussed." @default.
• W2016153757 created "2016-06-24" @default.
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• W2016153757 date "2012-10-01" @default.
• W2016153757 modified "2023-09-27" @default.
• W2016153757 title "Automated classification system for Bone Age X-ray images" @default.
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• W2016153757 doi "https://doi.org/10.1109/icsmc.2012.6377701" @default.
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