bibtext: @InProceedings{ Mis_STANLOC_MICCAI2024,
                   author = { Mishra, Divyanshu and Saha, Pramit and Zhao, He and Patey, Olga and Papageorghiou, Aris T. and Noble, J. Alison },
                   title = { { STAN-LOC: Visual Query-based Video Clip Localization for Fetal Ultrasound Sweep Videos } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15004 },
                   month = {October},
                   pages = { pending },
                }
abstract: Detecting standard frame clips in fetal ultrasound videos is
  crucial for accurate clinical assessment and diagnosis. It enables health-
  care professionals to evaluate fetal development, identify abnormalities,
  and monitor overall health with clarity and standardization. To aug-
  ment sonographer workflow and to detect standard frame clips, we in-
  troduce the task of Visual Query-based Video Clip Localization in med-
  ical video understanding. It aims to retrieve a video clip from a given
  ultrasound sweep that contains frames similar to a given exemplar frame
  of the required standard anatomical view. To solve the task, we propose
  STAN-LOC that consists of three main components: (a) a Query-Aware
  Spatio-Temporal Fusion Transformer that fuses information available in
  the visual query with the input video. This results in visual query-aware
  video features which we model temporally to understand spatio-temporal
  relationship between them. (b) a Multi-Anchor, View-Aware Contrastive
  loss to reduce the influence of inherent noise in manual annotations es-
  pecially at event boundaries and in videos featuring highly similar ob-
  jects. (c) a query selection algorithm during inference that selects the
  best visual query for a given video to reduce model’s sensitivity to the
  quality of visual queries. We apply STAN-LOC to the task of detect-
  ing standard-frame clips in fetal ultrasound heart sweeps given four-
  chamber view queries. Additionally, we assess the performance of our
  best model on PULSE [2] data for retrieving standard transventricular
  plane (TVP) in fetal head videos. STAN-LOC surpasses the state-of-the-
  art method by 22% in mtIoU. The code will be available upon acceptance
  at xxx.github.com.
title: STAN-LOC: Visual Query-based Video Clip Localization for Fetal Ultrasound Sweep Videos
authors: Mishra, Divyanshu Saha, Pramit Zhao, He Patey, Olga Papageorghiou, Aris T. Noble, J. Alison