RL Based Unsupervised Video Summarization Framework for Ultrasound Imaging
3rd International Workshop of Advances in Simplifying Medical Ultrasound, ASMUS 2022, held in Conjunction with 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
; 13565 LNCS:23-33, 2022.
Article
in English
| Scopus | ID: covidwho-2059734
ABSTRACT
The need for summarizing long medical scan videos for automatic triage in Emergency Departments and transmission of the summarized videos for telemedicine has gained significance during the COVID-19 pandemic. However, supervised learning schemes for summarizing videos are infeasible as manual labeling of scans for large datasets is impractical by frontline clinicians. This work presents a methodology to summarize ultrasound videos using completely unsupervised learning schemes and is validated on Lung Ultrasound videos. A Convolutional Autoencoder and a Transformer decoder is trained in an unsupervised reinforcement learning setup i.e., without supervised labels in the whole workflow. Novel precision and recall computation for ultrasound videos is also presented employing which high Precision and F1 scores of 64.36% and 35.87% with an average video compression rate of 78% is obtained when validated against clinically annotated cases. Even though demonstrated using lung ultrasound videos, our approach can be readily extended to other imaging modalities. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Convolutional autoencoder; Transformer; Ultrasound; Unsupervised reinforcement learning; Video summarization; Biological organs; Convolution; Convolutional neural networks; Decoding; Deep learning; Large dataset; Learning systems; Reinforcement learning; Ultrasonic imaging; Video recording; Auto encoders; Learning schemes; Lung ultrasound; Reinforcement learnings; Ultrasound imaging; Ultrasound videos; Image compression
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
3rd International Workshop of Advances in Simplifying Medical Ultrasound, ASMUS 2022, held in Conjunction with 25th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS