000			01417 am a22002653u 4500
042			_adc
100	1	0	_aYasrab, Robail _eauthor _92275
700	1	0	_aFu, Zeyu _eauthor _92276
700	1	0	_aDrukker, Lior _eauthor
700	1	0	_aLee, Lok Hin _eauthor
700	1	0	_aZhao, He _eauthor
700	1	0	_aPapageorghiou, Aris T. _eauthor
700	1	0	_aNoble, Alison J. _eauthor
245	0	0	_aEnd-to-end First Trimester Fetal Ultrasound Video Automated CRL and NT Segmentation
260			_c2022-04-28.
500			_a/pmc/articles/PMC7614066/
500			_a/pubmed/36643819
520			_aThis study presents a novel approach to automatic detection and segmentation of the Crown Rump Length (CRL) and Nuchal Translucency (NT), two essential measurements in the first trimester US scan. The proposed method automatically localises a standard plane within a video clip as defined by the UK Fetal Abnormality Screening Programme. A Nested Hourglass (NHG) based network performs semantic pixel-wise segmentation to extract NT and CRL structures. Our results show that the NHG network is faster (19.52% < GFlops than FCN32) and offers high pixel agreement (mean-IoU=80.74) with expert manual annotations.
540			_a
546			_aen
690			_aArticle
655	7		_aText _2local
786	0		_nProc IEEE Int Symp Biomed Imaging
856	4	1	_uhttp://dx.doi.org/10.1109/ISBI52829.2022.9761400 _zConnect to this object online.
999			_c2064 _d2064