title: A novel semi-automated method of tracking fetal movements.
abstract: We have designed software that can "look" at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut, a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software's ability to track movement. Two sonographers rated the results of our computer's 'vision' on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software's ability to track the fetus over time.
authors.forename: S
authors.initials: S
authors.lastname: Bhaskar
authors.forename: C
authors.initials: C
authors.lastname: Surlea
authors.forename: F
authors.initials: F
authors.lastname: Mone
authors.forename: P
authors.initials: P
authors.lastname: Milligan
authors.forename: S
authors.initials: S
authors.lastname: Ong
mesh_terms: D000465:Algorithms; D005260:Female; D005323:Fetal Monitoring / Q000379:methods*; D005324:Fetal Movement / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D011247:Pregnancy; D012984:Software; D014741:Video Recording / Q000379:methods*