Learn Fine-Grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent deep learning methods have improved results by directly encoding the appearance of the captured anatomy with the likelihood maps (i.e., heatmaps). How...

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Bibliographic Details
Main Authors:	Chen, C. (Author), Huang, Y. (Author), Huo, E.-Z (Author), Li, R. (Author), Miao, J. (Author), Ni, D. (Author), Qian, J. (Author), Shi, W. (Author), Yang, X. (Author), Zhou, G.-Q (Author)
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:	Active termination adaptive loss anatomic landmark Anatomical landmark detection Anatomical landmarks article awareness Deep learning exploration exploitation tradeoff Exploration exploitations female Female fetus echography hand Hand heating Heating heatmap regression human Humans Landmark detection Landmark localization Learning systems Learning to learn Localization accuracy Medical imaging Neural Networks, Computer Optimization pregnancy Pregnancy Prenatal ultrasound radiography Radiography reinforcement (psychology) reinforcement learning Reinforcement learning Ultrasonic applications X ray
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Learn Fine-Grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

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