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Title: Towards Whole Placenta Segmentation At Late Gestation Using Multi-View Ultrasound Images
Authors: Zimmera, VA
Gomeza, A
Skeltona, E
Toussainta, N
Zhanga, T
Khanala, B
Wrighta, R
Noh, Y
Ho, A
Matthewa, J
Hajnala, JV
Schnabela, JA
Issue Date: 10-Oct-2019
Publisher: Springer Verlag
Citation: Lecture Notes in Computer Science, 2019, 11768 pp. 628 - 636
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.
Appears in Collections:Dept of Mechanical Aerospace and Civil Engineering Research Papers

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