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Conference Paper
3D Reconstruction of Leg Bones from X-Ray Images using CNN-based Feature Analysis
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- Authors
- Hangkee Kim, Kisuk Lee, Dongchun Lee, Nakhoon Baek
- Issue Date
- 2019-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.669-672
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- 3D reconstruction of subject specific bones from X-Ray images is an important issue in a variety of medical applications such as diagnosis. We propose a method to reconstruct 3D leg bones from 2D X-Ray images using feature analysis. First, bounding boxes are detected by Convolutional Neural Network(CNN). Feature points and feature ellipses are extracted from them. Such features are aligned with feature information of 3D bone model. Then, the boundary of X-Ray is detected from aligned boundary of 3D model. The 3D model is fine-tuned by adjusting the Statistical Shape Model parameter. We believe that this method makes 3D modeling easier by improving the automatic detection of feature information compared to the manual landmark input method.
- KSP Keywords
- 3D bone model, 3d modeling, 3d reconstruction, Automatic Detection, Bounding Box, Convolution neural network(CNN), Feature Points, Feature analysis, Feature information, Leg bones, Medical Applications