Towards Unsupervised Ultrasound Video Clinical Quality Assessment with Multi-modality Data

He Zhao, Qingqing Zheng, Clare Teng, Robail Yasrab, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Video quality assurance is an important topic in obstetric ultrasound imaging to ensure that captured videos are suitable for biometry and fetal health assessment. Previously, one successful objective approach to automated ultrasound image quality assurance has considered it as a supervised learning task of detecting anatomical structures defined by a clinical protocol. In this paper, we propose an alternative and purely data-driven approach that makes effective use of both spatial and temporal information and the model learns from high-quality videos without any anatomy-specific annotations. This makes it attractive for potentially scalable generalisation. In the proposed model, a 3D encoder and decoder pair bi-directionally learns a spatio-temporal representation between the video space and the feature space. A zoom-in module is introduced to encourage the model to focus on the main object in a frame. A further design novelty is the introduction of two additional modalities in model training (sonographer gaze and optical flow derived from the video). Finally, our approach is applied to identify high-quality videos for fetal head circumference measurement in freehand second-trimester ultrasound scans. Extensive experiments are conducted, and the results demonstrate the effectiveness of our approach with an AUC of 0.911.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings
EditorsLinwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
PublisherSpringer Science and Business Media Deutschland GmbH
Pages228-237
Number of pages10
ISBN (Print)9783031164392
DOIs
StatePublished - 2022
Event25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 - Singapore, Singapore
Duration: 18 Sep 202222 Sep 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13434 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022
Country/TerritorySingapore
CitySingapore
Period18/09/2222/09/22

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