Title
Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images
Abstract
We propose a method to extract the human placenta at late gestation using multi-view 3D US images. This is the first step towards automatic quantification of placental volume and morphology from US images along the whole pregnancy beyond early stages (where the entire placenta can be captured with a single 3D US image). Our method uses 3D US images from different views acquired with a multi-probe system. A whole placenta segmentation is obtained from these images by using a novel technique based on 3D convolutional neural networks. We demonstrate the performance of our method on 3D US images of the placenta in the last trimester. We achieve a high Dice overlap of up to 0.8 with respect to manual annotations, and the derived placental volumes are comparable to corresponding volumes extracted from MR.
Year
DOI
Venue
2019
10.1007/978-3-030-32254-0_70
Lecture Notes in Computer Science
DocType
Volume
ISSN
Conference
11768
0302-9743
Citations 
PageRank 
References 
0
0.34
0
Authors
12
Name
Order
Citations
PageRank
Veronika A. M. Zimmer1177.66
Alberto Gómez2104.28
Emily Skelton302.03
Nicolas Toussaint4579.19
Tong Zhang521.37
Bishesh Khanal600.68
R Wright71187.56
Yohan Noh811315.61
Alison Ho901.69
Jacqueline Matthew10325.18
Jo Hajnal111796119.03
Julia A Schnabel121978151.49