Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images
Leroy G, Rueckert D, Alansary A (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12449 LNCS
Pages Range: 177-186
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Lima, PER
ISBN: 9783030668426
DOI: 10.1007/978-3-030-66843-3_18
Abstract
Accurate detection of anatomical landmarks is an essential step in several medical imaging tasks. We propose a novel communicative multi-agent reinforcement learning (C-MARL) system to automatically detect landmarks in 3D medical scans. C-MARL enables the agents to learn explicit communication channels, as well as implicit communication signals by sharing certain weights of the architecture among all the agents. The proposed approach is evaluated on two brain imaging datasets from adult magnetic resonance imaging (MRI) and fetal ultrasound scans. Our experiments show that involving multiple cooperating agents by learning their communication with each other outperforms previous approaches using single agents.
Involved external institutions
United Kingdom (GB)How to cite
APA:
Leroy, G., Rueckert, D., & Alansary, A. (2020). Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images. In Seyed Mostafa Kia, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, Jane Maryam Rondina, Chantal Tax, Hongzhi Wang, Thomas Wolfers, Saima Rathore, Madhura Ingalhalikar (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 177-186). Lima, PER: Springer Science and Business Media Deutschland GmbH.
MLA:
Leroy, Guy, Daniel Rueckert, and Amir Alansary. "Communicative Reinforcement Learning Agents for Landmark Detection in Brain Images." Proceedings of the 3rd International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and 2nd International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, Lima, PER Ed. Seyed Mostafa Kia, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, Jane Maryam Rondina, Chantal Tax, Hongzhi Wang, Thomas Wolfers, Saima Rathore, Madhura Ingalhalikar, Springer Science and Business Media Deutschland GmbH, 2020. 177-186.
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