Complete Fetal Head Compounding from Multi-view 3D Ultrasound
Wright R, Toussaint N, Gomez A, Zimmer V, Khanal B, Matthew J, Skelton E, Kainz B, Rueckert D, Hajnal JV, Schnabel JA (2019)
Publication Type: Conference contribution
Publication year: 2019
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 11766 LNCS
Pages Range: 384-392
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Shenzhen, CHN
ISBN: 9783030322472
DOI: 10.1007/978-3-030-32248-9_43
Abstract
Ultrasound (US) images suffer from artefacts which limit its diagnostic value, notably acoustic shadow. Shadows are dependent on probe orientation, with each view giving a distinct, partial view of the anatomy. In this work, we fuse the partially imaged fetal head anatomy, acquired from numerous views, into a single coherent compounding of the full anatomy. Firstly, a stream of freehand 3D US images is acquired, capturing as many different views as possible. The imaged anatomy at each time-point is then independently aligned to a canonical pose using an iterative spatial transformer network (iSTN), making our approach robust to fast fetal and probe motion. Secondly, images are fused by averaging only the best (most salient) features from all images, producing a more detailed compounding. Finally, the compounding is iteratively refined using a groupwise registration approach. We evaluate our compounding approach quantitatively and qualitatively, comparing it with average compounding and individual US frames. We also evaluate our alignment accuracy using two physically attached probes, that capture separate views simultaneously, providing ground-truth. Lastly, we demonstrate the potential clinical impact of our method for assessing cranial, facial and external ear abnormalities, with automated atlas-based masking and 3D volume rendering.
Authors with CRIS profile
Involved external institutions
King’s College London
United Kingdom (GB)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
United Kingdom (GB)
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
How to cite
APA:
Wright, R., Toussaint, N., Gomez, A., Zimmer, V., Khanal, B., Matthew, J.,... Schnabel, J.A. (2019). Complete Fetal Head Compounding from Multi-view 3D Ultrasound. In Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 384-392). Shenzhen, CHN: Springer Science and Business Media Deutschland GmbH.
MLA:
Wright, Robert, et al. "Complete Fetal Head Compounding from Multi-view 3D Ultrasound." Proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, Shenzhen, CHN Ed. Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou, Springer Science and Business Media Deutschland GmbH, 2019. 384-392.
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