Automatic Segmentation of the Fetus in 3D Magnetic Resonance Images Using Deep Learning: Accurate and Fast Fetal Volume Quantification for Clinical Use

Magnetic resonance imaging (MRI) provides images for estimating fetal volume and weight, but manual delineations are time consuming. The aims were to (1) validate an algorithm to automatically quantify fetal volume by MRI; (2) compare fetal weight by Hadlock’s formulas to that of MRI; and (3) quanti...

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Veröffentlicht in:	Pediatric cardiology Jg. 44; H. 6; S. 1311 - 1318
Hauptverfasser:	Ryd, Daniel, Nilsson, Amanda, Heiberg, Einar, Hedström, Erik
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2023 Springer Springer Nature B.V
Schlagworte:	Agreements Algorithms Amniotic fluid Cardiac Surgery Cardiology Clinical Medicine Comparative analysis Coronary vessels Deep Learning Engineering and Technology Fetal Weight Fetus - diagnostic imaging Fetuses Gestational Age Humans Klinisk medicin Magnetic Resonance Imaging Medical and Health Sciences Medical Engineering Medical Imaging Medicin och hälsovetenskap Medicine Medicine & Public Health Medicinsk bildvetenskap Medicinteknik Neural networks Physiological aspects Placenta Pregnancy R&D Radiologi och bildbehandling Radiology and Medical Imaging Research & development Teknik Three dimensional imaging Ultrasonic imaging Umbilical cord Vascular Surgery Veins & arteries Sweden Fetal weight Fetal cardiovascular magnetic resonance imaging Prenatal diagnosis
ISSN:	0172-0643, 1432-1971, 1432-1971
Online-Zugang:	Volltext
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