TY - JOUR
T1 - Fast fetal head compounding from multi-view 3D ultrasound
AU - Wright, Robert
AU - Gomez, Alberto
AU - Zimmer, Veronika A.
AU - Toussaint, Nicolas
AU - Khanal, Bishesh
AU - Matthew, Jacqueline
AU - Skelton, Emily
AU - Kainz, Bernhard
AU - Rueckert, Daniel
AU - Hajnal, Joseph V.
AU - Schnabel, Julia A.
N1 - Funding Information:
This work was supported by the Wellcome Trust IEH Award [ 102431 ], by the Wellcome/EPSRC Centre for Medical Engineering [ WT203148/Z/16/Z ] and by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.
Funding Information:
This work was supported by the Wellcome Trust IEH Award [102431], by the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z] and by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas’ NHS Foundation Trust and King's College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.
Publisher Copyright:
© 2023
PY - 2023/10
Y1 - 2023/10
N2 - The diagnostic value of ultrasound images may be limited by the presence of artefacts, notably acoustic shadows, lack of contrast and localised signal dropout. Some of these artefacts are dependent on probe orientation and scan technique, with each image giving a distinct, partial view of the imaged anatomy. In this work, we propose a novel method to fuse the partially imaged fetal head anatomy, acquired from numerous views, into a single coherent 3D volume of the full anatomy. Firstly, a stream of freehand 3D US images is acquired using a single probe, capturing as many different views of the head as possible. The imaged anatomy at each time-point is then independently aligned to a canonical pose using a recurrent spatial transformer network, making our approach robust to fast fetal and probe motion. Secondly, images are fused by averaging only the most consistent and salient features from all images, producing a more detailed compounding, while minimising artefacts. We evaluated our method quantitatively and qualitatively, using image quality metrics and expert ratings, yielding state of the art performance in terms of image quality and robustness to misalignments. Being online, fast and fully automated, our method shows promise for clinical use and deployment as a real-time tool in the fetal screening clinic, where it may enable unparallelled insight into the shape and structure of the face, skull and brain.
AB - The diagnostic value of ultrasound images may be limited by the presence of artefacts, notably acoustic shadows, lack of contrast and localised signal dropout. Some of these artefacts are dependent on probe orientation and scan technique, with each image giving a distinct, partial view of the imaged anatomy. In this work, we propose a novel method to fuse the partially imaged fetal head anatomy, acquired from numerous views, into a single coherent 3D volume of the full anatomy. Firstly, a stream of freehand 3D US images is acquired using a single probe, capturing as many different views of the head as possible. The imaged anatomy at each time-point is then independently aligned to a canonical pose using a recurrent spatial transformer network, making our approach robust to fast fetal and probe motion. Secondly, images are fused by averaging only the most consistent and salient features from all images, producing a more detailed compounding, while minimising artefacts. We evaluated our method quantitatively and qualitatively, using image quality metrics and expert ratings, yielding state of the art performance in terms of image quality and robustness to misalignments. Being online, fast and fully automated, our method shows promise for clinical use and deployment as a real-time tool in the fetal screening clinic, where it may enable unparallelled insight into the shape and structure of the face, skull and brain.
KW - Compounding
KW - Deep learning
KW - Fast
KW - Fetal
KW - Fusion
KW - Laplacian pyramid
KW - Multi view
KW - Online
KW - Pose
KW - Registration
KW - Reinforcement learning
KW - Ultrasound
KW - US
UR - http://www.scopus.com/inward/record.url?scp=85165528184&partnerID=8YFLogxK
U2 - 10.1016/j.media.2023.102793
DO - 10.1016/j.media.2023.102793
M3 - Article
C2 - 37482034
AN - SCOPUS:85165528184
SN - 1361-8415
VL - 89
JO - Medical Image Analysis
JF - Medical Image Analysis
M1 - 102793
ER -