Deep Bv: A Fully Automated System for Brain Ventricle Localization and Segmentation In 3D Ultrasound Images of Embryonic Mice

Ziming Qiu, Jack Langerman, Nitin Nair, Orlando Aristizabal, Jonathan Mamou, Daniel H. Turnbull, Jeffrey Ketterling, Yao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Volumetric analysis of brain ventricle (BV) structure is a key tool in the study of central nervous system development in embryonic mice. High-frequency ultrasound (HFU) is the only non-invasive, real-time modality available for rapid volumetric imaging of embryos in utero. However, manual segmentation of the BV from HFU volumes is tedious, time-consuming, and requires specialized expertise. In this paper, we propose a novel deep learning based BV segmentation system for whole-body HFU images of mouse embryos. Our fully automated system consists of two modules: localization and segmentation. It first applies a volumetric convolutional neural network on a 3D sliding window over the entire volume to identify a 3D bounding box containing the entire BV. It then employs a fully convolutional network to segment the detected bounding box into BV and background. The system achieves a Dice Similarity Coefficient (DSC) of 0.8956 for BV segmentation on an unseen 111 HFU volume test set surpassing the previous state-of-the-art method (DSC of 0.7119) by a margin of 25%.

Original languageEnglish (US)
Title of host publication2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538659168
DOIs
StatePublished - Jan 16 2019
Event2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Philadelphia, United States
Duration: Dec 1 2018 → …

Publication series

Name2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings

Conference

Conference2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018
CountryUnited States
CityPhiladelphia
Period12/1/18 → …

ASJC Scopus subject areas

  • Signal Processing
  • Health Informatics

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    Qiu, Z., Langerman, J., Nair, N., Aristizabal, O., Mamou, J., Turnbull, D. H., Ketterling, J., & Wang, Y. (2019). Deep Bv: A Fully Automated System for Brain Ventricle Localization and Segmentation In 3D Ultrasound Images of Embryonic Mice. In 2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings [8615610] (2018 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPMB.2018.8615610