Evaluating reinforcement learning agents for anatomical landmark detection

Alansary A, Oktay O, Li Y, Le Folgoc L, Hou B, Vaillant G, Kamnitsas K, Vlontzos A, Glocker B, Kainz B, Rueckert D (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Medical Image Analysis Elsevier

Book Volume: 53

Pages Range: 156-164

DOI: 10.1016/j.media.2019.02.007

Abstract

Automatic detection of anatomical landmarks is an important step for a wide range of applications in medical image analysis. Manual annotation of landmarks is a tedious task and prone to observer errors. In this paper, we evaluate novel deep reinforcement learning (RL) strategies to train agents that can precisely and robustly localize target landmarks in medical scans. An artificial RL agent learns to identify the optimal path to the landmark by interacting with an environment, in our case 3D images. Furthermore, we investigate the use of fixed- and multi-scale search strategies with novel hierarchical action steps in a coarse-to-fine manner. Several deep Q-network (DQN) architectures are evaluated for detecting multiple landmarks using three different medical imaging datasets: fetal head ultrasound (US), adult brain and cardiac magnetic resonance imaging (MRI). The performance of our agents surpasses state-of-the-art supervised and RL methods. Our experiments also show that multi-scale search strategies perform significantly better than fixed-scale agents in images with large field of view and noisy background such as in cardiac MRI. Moreover, the novel hierarchical steps can significantly speed up the searching process by a factor of 4–5 times.

Authors with CRIS profile

Bernhard Kainz

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB)

How to cite

APA:

Alansary, A., Oktay, O., Li, Y., Le Folgoc, L., Hou, B., Vaillant, G.,... Rueckert, D. (2019). Evaluating reinforcement learning agents for anatomical landmark detection. Medical Image Analysis, 53, 156-164. https://dx.doi.org/10.1016/j.media.2019.02.007

MLA:

Alansary, Amir, et al. "Evaluating reinforcement learning agents for anatomical landmark detection." Medical Image Analysis 53 (2019): 156-164.

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