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Cerebral Aneurysm Detection

Overview of attention for book
Cover of 'Cerebral Aneurysm Detection'

Table of Contents

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    Book Overview
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    Chapter 1 Cerebral Aneurysm Detection and Analysis Challenge 2020 (CADA)
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    Chapter 2 CADA: Clinical Background and Motivation
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    Chapter 3 Deep Learning-Based 3D U-Net Cerebral Aneurysm Detection
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    Chapter 4 Detect and Identify Aneurysms Based on Adjusted 3D Attention UNet
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    Chapter 5 A$$\nu $$-Net: Automatic Detection and Segmentation of Aneurysm
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    Chapter 6 3D Attention U-Net with Pretraining: A Solution to CADA-Aneurysm Segmentation Challenge
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    Chapter 7 Exploring Large Context for Cerebral Aneurysm Segmentation
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    Chapter 8 CADA Challenge: Rupture Risk Assessment Using Computational Fluid Dynamics
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    Chapter 9 Cerebral Aneurysm Rupture Risk Estimation Using XGBoost and Fully Connected Neural Network
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    Chapter 10 Intracranial Aneurysm Rupture Risk Estimation Utilizing Vessel-Graphs and Machine Learning
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    Chapter 11 Intracranial Aneurysm Rupture Prediction with Computational Fluid Dynamics Point Clouds
Attention for Chapter 4: Detect and Identify Aneurysms Based on Adjusted 3D Attention UNet
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Citations

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4 Mendeley
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Chapter title
Detect and Identify Aneurysms Based on Adjusted 3D Attention UNet
Chapter number 4
Book title
Cerebral Aneurysm Detection
Published by
Springer, Cham, April 2021
DOI 10.1007/978-3-030-72862-5_4
Book ISBNs
978-3-03-072861-8, 978-3-03-072862-5
Authors

Yizhuan Jia, Weibin Liao, Yi Lv, Ziyu Su, Jiaqi Dou, Zhongwei Sun, Xuesong Li, Jia, Yizhuan, Liao, Weibin, Lv, Yi, Su, Ziyu, Dou, Jiaqi, Sun, Zhongwei, Li, Xuesong

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Lecturer 1 25%
Unknown 2 50%
Readers by discipline Count As %
Nursing and Health Professions 1 25%
Engineering 1 25%
Unknown 2 50%

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