AUTOMATIC DETECTION OF LOCAL FETAL BRAIN STRUCTURES IN ULTRASOUND IMAGES

AUTOMATIC DETECTION OF LOCAL FETAL BRAIN STRUCTURES IN ULTRASOUND IMAGES

Although ultrasound imaging is the main modality to study fetal growth, the analysis of such images is an under-studied area of research especially using 3D ultrasound. In this paper we propose an automatic technique to locate four local fetal brain structures in 3D ultrasound images. Clinically, th...

Bibliografski detalji
Glavni autori:	Yaqub, M, Napolitano, R, Ioannou, C, Papageorghiou, A, Noble, J, IEEE
Format:	Journal article
Jezik:	English
Izdano:	2012

Slični predmeti

Fusion of 3D ultrasound images of the fetal femur improves boundary definition and volume measurement.
od: Yaqub, M, i dr.
Izdano: (2013)

Learning-based prediction of gestational age from ultrasound images of the fetal brain
od: Namburete, A, i dr.
Izdano: (2015)

A Novel Local-Phase Method of Automatic Atlas Construction in Fetal Ultrasound
od: Fathima, S, i dr.
Izdano: (2011)

The effect of maternal body mass index on fetal ultrasound image quality
od: Yaqub, M, i dr.
Izdano: (2021)

QUALITY CONTROL OF FETAL ULTRASOUND IMAGES: DETECTION OF ABDOMEN ANATOMICAL LANDMARKS USING ADABOOST
od: Rahmatullah, B, i dr.
Izdano: (2011)

Predicting fetal neurodevelopmental age from ultrasound images
od: Namburete, A, i dr.
Izdano: (2014)

Localizing Cardiac Structures in Fetal Heart Ultrasound Video
od: Bridge, C, i dr.
Izdano: (2017)

Self-supervised ultrasound to MRI fetal brain image synthesis
od: Jiao, J, i dr.
Izdano: (2020)

A framework for analysis of linear ultrasound videos to detect fetal presentation and heartbeat
od: Maraci, M, i dr.
Izdano: (2017)

Label efficient localization of fetal brain biometry planes in ultrasound through metric learning
od: Gao, Y, i dr.
Izdano: (2020)

Image Analysis Using Machine Learning: Anatomical landmarks detection in fetal ultrasound images
od: Rahmatullah, B, i dr.
Izdano: (2012)

Quality improvement programme of ultrasound based fetal anatomy screening using large scale clinical audit
od: Yaqub, M, i dr.
Izdano: (2018)

Automated 3D ultrasound image analysis for first trimester assessment of fetal health
od: Ryou, H, i dr.
Izdano: (2019)

REGULARISED FEATURE-BASED FUZZY CONNECTEDNESS SEGMENTATION OF ULTRASOUND IMAGES FOR FETAL SOFT TISSUE QUANTIFICATION ACROSS GESTATION
od: Rueda, S, i dr.
Izdano: (2012)

Multi-task CNN for structural semantic segmentation in 3D fetal brain ultrasound
od: Venturini, L, i dr.
Izdano: (2020)

A systematic review of methodology used in studies aimed at creating charts of fetal brain structures
od: Donadono, V, i dr.
Izdano: (2021)

Calibrated Bayesian neural networks to estimate gestational age and its uncertainty on fetal brain ultrasound images
od: Lee, LH, i dr.
Izdano: (2020)

A deep learning solution for automatic fetal neurosonographic diagnostic plane verification using clinical standard constraints
od: Yaqub, M, i dr.
Izdano: (2017)

Captioning ultrasound images automatically
od: Alsharid, M, i dr.
Izdano: (2019)

Surface area measurement using rendered three-dimensional ultrasound imaging: an in-vitro phantom study.
od: Ioannou, C, i dr.
Izdano: (2011)

Surface area measurement using rendered three-dimensional ultrasound imaging: An in-vitro phantom study
od: Ioannou, C, i dr.
Izdano: (2011)

A dual adversarial calibration framework for automatic fetal brain biometry
od: Gao, Y, i dr.
Izdano: (2021)

Plane Localization in 3-D Fetal Neurosonography for Longitudinal Analysis of the Developing Brain
od: Yaqub, M, i dr.
Izdano: (2015)

VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography
od: Huang, R, i dr.
Izdano: (2018)

Toward point-of-care ultrasound estimation of fetal gestational age from the trans-cerebellar diameter using CNN-based ultrasound image analysis.
od: Maraci, MA, i dr.
Izdano: (2020)

A Systematic Review of Methodology Used in Studies Aimed at Creating Charts of Fetal Brain Structures
od: Vera Donadono, i dr.
Izdano: (2021-05-01)

Anatomy-aware self-supervised fetal MRI synthesis from unpaired ultrasound images
od: Jiao, J, i dr.
Izdano: (2019)

ScanNav (R) audit: an AI-powered screening assistant for fetal anatomical ultrasound
od: Yaqub, M, i dr.
Izdano: (2021)

TOWARDS 3D REGISTRATION OF FETAL BRAIN MRI AND ULTRASOUND
od: Kuklisova-Murgasova, M, i dr.
Izdano: (2012)

Fetal abnormalities detected during third-trimester ultrasound for fetal growth
od: Drukker, L, i dr.
Izdano: (2021)

Registration of 3D fetal brain US and MRI.
od: Kuklisova-Murgasova, M, i dr.
Izdano: (2012)

Automated characteriazation of the fetal heart in ultrasound images using fully convolutional neural networks
od: Sundaresan, V, i dr.
Izdano: (2017)

International standards for fetal brain structures based on serial ultrasound measurements from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project
od: Napolitano, R, i dr.
Izdano: (2020)

Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks
od: Alsharid, M, i dr.
Izdano: (2022)

Automated annotation and quantitative description of ultrasound videos of the fetal heart
od: Bridge, C, i dr.
Izdano: (2016)

Integration of local and global features for anatomical object detection in ultrasound.
od: Rahmatullah, B, i dr.
Izdano: (2012)

The effect of maternal vitamin D concentration on fetal bone.
od: Ioannou, C, i dr.
Izdano: (2012)

Automatic probe movement guidance for freehand obstetric ultrasound
od: Droste, R, i dr.
Izdano: (2020)

Anatomy-aware contrastive representation learning for fetal ultrasound
od: Fu, Z, i dr.
Izdano: (2023)

Intra- and interobserver variability in fetal ultrasound measurements.
od: Sarris, I, i dr.
Izdano: (2012)