Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation

Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation

Accurate screening for septal defects is important for supporting radiologists' interpretative work. Some previous studies have proposed semantic segmentation and object detection approaches to carry out fetal heart detection; unfortunately, the models could not segment different objects of the...

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Bibliographic Details
Main Authors: Siti Nurmaini, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Annisa Darmawahyuni, Adithia Jovandy, Firdaus Firdaus, Bambang Tutuko, Rossi Passarella
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Congenital heart disease
fetal echocardiography
mask-RCNN
septal defects
multiclass instance segmentation
Online Access:https://ieeexplore.ieee.org/document/9241786/

Internet

https://ieeexplore.ieee.org/document/9241786/

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