Cross Attention Squeeze Excitation Network (CASE-Net) for Whole Body Fetal MRI Segmentation

Segmentation of the fetus from 2-dimensional (2D) magnetic resonance imaging (MRI) can aid radiologists with clinical decision making for disease diagnosis. Machine learning can facilitate this process of automatic segmentation, making diagnosis more accurate and user independent. We propose a deep...

Disgrifiad llawn

Manylion Llyfryddiaeth

Prif Awduron:	Justin Lo, Saiee Nithiyanantham, Jillian Cardinell, Dylan Young, Sherwin Cho, Abirami Kirubarajan, Matthias W. Wagner, Roxana Azma, Steven Miller, Mike Seed, Birgit Ertl-Wagner, Dafna Sussman
Fformat:	Artigo
Iaith:	Inglês
Cyhoeddwyd:	MDPI AG 2021-06-01
Cyfres:	Sensors
Pynciau:	deep learning fetal MRI convolutional neural networks automatic segmentation squeeze-and-excitation attention mechanisms
Mynediad Ar-lein:	https://www.mdpi.com/1424-8220/21/13/4490
Tagiau:	Ychwanegu Tag Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!