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
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
More filters
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
More filters
Book ChapterDOI
Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound
Dong Ni,Tianmei Li,Xin Yang,Jing Qin,Shengli Li,Chien-Ting Chin,Shuyuan Ouyang,Tianfu Wang,Siping Chen +8 more
TL;DR: Experimental results on 100 fetal abdomen videos show that the first automatic solution for localizing fetal abdominal standard plane FASP in consecutive 2D ultrasound images significantly outperforms traditional methods that only use local detector.
Book ChapterDOI
Motion Corrected 3D Reconstruction of the Fetal Thorax from Prenatal MRI
Bernhard Kainz,Christina Malamateniou,Maria Murgasova,Kevin Keraudren,Mary A. Rutherford,Joseph V. Hajnal,Daniel Rueckert +6 more
TL;DR: A semi-automatic method for analysis of the fetal thorax in genuine three-dimensional volumes and shows that the computed segmentations and the manual ground truth correlate well with the recorded values in literature.
Journal ArticleDOI
Automated Screening of Fetal Heart Chambers from 2-D Ultrasound Cine-Loop Sequences
Journal ArticleDOI
Left ventricle segmentation in fetal echocardiography using a multi-texture active appearance model based on the steered Hermite transform
Lorena Vargas-Quintero,Boris Escalante-Ramrez,Lisbeth Camargo Marn,Mario Guzmn Huerta,Fernando Armbula Cosio,Hctor Borboa Olivares +5 more
TL;DR: Typical issues found in fetal cardiac ultrasound images such as different orientations and shape variations of the heart cavities can be easily handled with the designed method.
Journal ArticleDOI
Echocardiographic Image Sequence Segmentation and Analysis Using Self-Organizing Maps
TL;DR: A new approach for echocardiographic image sequence segmentation using the self-organizing maps to approximate the probability density function of the image patterns and was validated successfully by physicians.