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@article{Skelton:2021:10.1016/j.radi.2020.11.006,
author = {Skelton, E and Matthew, J and Li, Y and Khanal, B and Martinez, JJC and Toussaint, N and Gupta, C and Knight, C and Kainz, B and Hajnal, JV and Rutherford, M},
doi = {10.1016/j.radi.2020.11.006},
journal = {Radiography},
pages = {519--526},
title = {Towards automated extraction of 2D standard fetal head planes from 3D ultrasound acquisitions: A clinical evaluation and quality assessment comparison},
url = {http://dx.doi.org/10.1016/j.radi.2020.11.006},
volume = {27},
year = {2021}
}

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TY  - JOUR
AB  - IntroductionClinical evaluation of deep learning (DL) tools is essential to compliment technical accuracy metrics. This study assessed the image quality of standard fetal head planes automatically-extracted from three-dimensional (3D) ultrasound fetal head volumes using a customised DL-algorithm.MethodsTwo observers retrospectively reviewed standard fetal head planes against pre-defined image quality criteria. Forty-eight images (29 transventricular, 19 transcerebellar) were selected from 91 transabdominal fetal scans (mean gestational age = 26 completed weeks, range = 20+5–32+3 weeks). Each had two-dimensional (2D) manually-acquired (2D-MA), 3D operator-selected (3D-OS) and 3D-DL automatically-acquired (3D-DL) images. The proportion of adequate images from each plane and modality, and the number of inadequate images per plane was compared for each method. Inter and intra-observer agreement of overall image quality was calculated.ResultsSixty-seven percent of 3D-OS and 3D-DL transventricular planes were adequate quality. Forty-five percent of 3D-OS and 55% of 3D-DL transcerebellar planes were adequate.Seventy-one percent of 3D-OS and 86% of 3D-DL transventricular planes failed with poor visualisation of intra-cranial structures. Eighty-six percent of 3D-OS and 80% of 3D-DL transcerebellar planes failed due to inadequate visualisation of cerebellar hemispheres. Image quality was significantly different between 2D and 3D, however, no significant difference between 3D-modalities was demonstrated (p < 0.005). Inter-observer agreement of transventricular plane adequacy was moderate for both 3D-modalities, and weak for transcerebellar planes.ConclusionThe 3D-DL algorithm can automatically extract standard fetal head planes from 3D-head volumes of comparable quality to operator-selected planes. Image quality in 3D is inferior to corresponding 2D planes, likely due to limitations with 3D-technology and acquisition technique.Implications for practiceAutomated image
AU  - Skelton,E
AU  - Matthew,J
AU  - Li,Y
AU  - Khanal,B
AU  - Martinez,JJC
AU  - Toussaint,N
AU  - Gupta,C
AU  - Knight,C
AU  - Kainz,B
AU  - Hajnal,JV
AU  - Rutherford,M
DO  - 10.1016/j.radi.2020.11.006
EP  - 526
PY  - 2021///
SN  - 1078-8174
SP  - 519
TI  - Towards automated extraction of 2D standard fetal head planes from 3D ultrasound acquisitions: A clinical evaluation and quality assessment comparison
T2  - Radiography
UR  - http://dx.doi.org/10.1016/j.radi.2020.11.006
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000640791900038&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.sciencedirect.com/science/article/pii/S1078817420302352?via%3Dihub
UR  - http://hdl.handle.net/10044/1/91873
VL  - 27
ER  -

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