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An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
[article]
2020
arXiv
pre-print
Cephalometric tracing method is usually used in orthodontic diagnosis and treat-ment planning. In this paper, we propose a deep learning based framework to au-tomatically detect anatomical landmarks in cephalometric X-ray images. We train the deep encoder-decoder for landmark detection, and combine global landmark configuration with local high-resolution feature responses. The proposed frame-work is based on 2-stage u-net, regressing the multi-channel heatmaps for land-mark detection. In this
arXiv:1906.07549v2
fatcat:kiflhrcgnrfvhc2mti66ifcdae