Journal ArticleDOI
Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects.
Jordina Torrents-Barrena,Gemma Piella,Narcís Masoller,Eduard Gratacós,Elisenda Eixarch,Mario Ceresa,Miguel Ángel González Ballester +6 more
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TLDR
This review covers state‐of‐the‐art segmentation and classification methodologies for the whole fetus and, more specifically, the fetal brain, lungs, liver, heart and placenta in magnetic resonance imaging and (3D) ultrasound for the first time.About:
This article is published in Medical Image Analysis.The article was published on 2019-01-01. It has received 70 citations till now.read more
Citations
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Journal ArticleDOI
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation
Ran Gu,Guotai Wang,Tao Song,Rui Huang,Michael Aertsen,Jan Deprest,Sebastien Ourselin,Tom Vercauteren,Shaoting Zhang +8 more
TL;DR: CA-Net as mentioned in this paper proposes a joint spatial attention module to make the network focus more on the foreground region and a novel channel attention module is proposed to adaptively recalibrate channel-wise feature responses and highlight the most relevant feature channels.
Journal ArticleDOI
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation
Ran Gu,Guotai Wang,Tao Song,Rui Huang,Michael Aertsen,Jan Deprest,Sebastien Ourselin,Tom Vercauteren,Shaoting Zhang +8 more
TL;DR: This work makes extensive use of multiple attentions in a CNN architecture and proposes a comprehensive attention-based CNN (CA-Net) for more accurate and explainable medical image segmentation that is aware of the most important spatial positions, channels and scales at the same time.
Journal ArticleDOI
A New Model for Brain Tumor Detection Using Ensemble Transfer Learning and Quantum Variational Classifier
Javeria Amin,Muhammad Almas Anjum,Muhammad Sharif,Saima Jabeen,Seifedine Kadry,Pablo Moreno Ger +5 more
TL;DR: Deep features are extracted from the inceptionv3 model, in which score vector is acquired from softmax and supplied to the quantum variational classifier (QVR) for discrimination between glioma, meningiomas, no tumor, and pituitary tumor to prove the proposed model's effectiveness.
Journal ArticleDOI
RLDS: An explainable residual learning diagnosis system for fetal congenital heart disease
TL;DR: Wang et al. as discussed by the authors proposed a simple yet effective residual learning diagnosis system (RLDS) for diagnosing fetal CHD to improve diagnostic accuracy, which adopts convolutional neural networks to extract discriminative features of the fetal cardiac anatomical structures.
Journal ArticleDOI
Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation
Siti Nurmaini,Muhammad Naufal Rachmatullah,Ade Iriani Sapitri,Annisa Darmawahyuni,Adithia Jovandy,Firdaus Firdaus,Bambang Tutuko,Rossi Passarella +7 more
TL;DR: The results suggest that the model used has a high potential to help cardiologists complete the initial screening for fetal congenital heart disease and a strong correlation between the predicted septal defects and ground truth as a mean average precision (mAP).
References
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Journal ArticleDOI
Risk stratification for congenital diaphragmatic hernia by factors within 24 h after birth
Keita Terui,Kouji Nagata,Yutaka Kanamori,S. Takahashi,Masahiro Hayakawa,Hiroomi Okuyama,Noboru Inamura,Hideo Yoshida,Tomoaki Taguchi,Noriaki Usui +9 more
TL;DR: A simple risk stratification system based on Ap1 and best OI was capable of predicting mortality well, and patients were classified into three risk categories.
Journal ArticleDOI
Fetal laser therapy: applications in the management of fetal pathologies
TL;DR: Management options discussed here are laser release of amniotic bands, laser coagulation of the placental or fetal tumor feeding vessels and laser therapy by fetal cystoscopy.
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Quantifying and modelling tissue maturation in the living human fetal brain.
TL;DR: The aim of this paper is to provide a review of the current research into MR imaging of the living fetal brain with the aim of motivating improved interfaces between the two fields.
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Computer-Aided Fetal Cardiac Scanning using 2D Ultrasound: Perspectives of Fetal Heart Biometry
TL;DR: This paper attempts to provide computer aided automated screening of second trimester fetal chambers using 2D ultrasound cine loop sequences by introducing automated location of fetal heart chamber with histogram-based segmentation.
Proceedings ArticleDOI
A template-to-slice block matching approach for automatic localization of brain in fetal MRI
TL;DR: A template-to-slice block matching technique that matches a spatiotemporal atlas of the fetal brain to the corresponding section of the brain in each 2D fetal MRI scan is developed that can be used for automatic localization of fetal brain as the first step of fetal MRI analysis pipeline.