Ultrasound Video Summarization Using Deep Reinforcement Learning
Liu T, Meng Q, Vlontzos A, Tan J, Rueckert D, Kainz B (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12263 LNCS
Pages Range: 483-492
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: 9783030597153
DOI: 10.1007/978-3-030-59716-0_46
Abstract
Video is an essential imaging modality for diagnostics, e.g. in ultrasound imaging, for endoscopy, or movement assessment. However, video hasn’t received a lot of attention in the medical image analysis community. In the clinical practice, it is challenging to utilise raw diagnostic video data efficiently as video data takes a long time to process, annotate or audit. In this paper we introduce a novel, fully automatic video summarization method that is tailored to the needs of medical video data. Our approach is framed as reinforcement learning problem and produces agents focusing on the preservation of important diagnostic information. We evaluate our method on videos from fetal ultrasound screening, where commonly only a small amount of the recorded data is used diagnostically. We show that our method is superior to alternative video summarization methods and that it preserves essential information required by clinical diagnostic standards.
Authors with CRIS profile
Involved external institutions
United Kingdom (GB)How to cite
APA:
Liu, T., Meng, Q., Vlontzos, A., Tan, J., Rueckert, D., & Kainz, B. (2020). Ultrasound Video Summarization Using Deep Reinforcement Learning. In Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 483-492). Lima, PER: Springer Science and Business Media Deutschland GmbH.
MLA:
Liu, Tianrui, et al. "Ultrasound Video Summarization Using Deep Reinforcement Learning." Proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, Lima, PER Ed. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, Springer Science and Business Media Deutschland GmbH, 2020. 483-492.
BibTeX: Download