Skip to main content

Advanced Search

Projected result for your current search: 0

Search Operators:

You can use operators in your search query to narrow down your results even more. Click on the search operator to see an explanation of how it works.
Finds documents with exactly this word group, in exactly this word order and spelling (e.g. "employer branding").
Finds documents with both search terms (e.g. sales AND bonus).
Finds documents with one or the other search term (e.g. porsche OR volkswagen).
Finds documents with all search terms. Blank space is understood as AND (e.g. man robot production).
Finds documents with no appearance of the word behind NOT (e.g. ford NOT "harrison ford").
Finds documents where the search term is mentioned at least "n" times."n" may be any number (e.g. COUNT(gear)>8).
Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Finds documents with the search term in different spellings. "?" allows only one character (e.g. organi?ation).
Special characters are understood as AND (e.g. Miller Bros. & Sons).

Semantic Search

powered by (Link opens in a new window)
loading …
Log in
Top

Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Authors
Yongjie Duan
Jianjiang Feng
Jiwen Lu
Jie Zhou
Published in
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges
Publisher
Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Cardiovascular disease caused by coronary artery disease (CAD) is one of the most common causes of death worldwide. Coronary artery segmentation has attracted increasing attention since it is useful for better visualization and diagnosis. Conventional lumen segmentation methods basically describe vessels by a rough tubular model, thus presenting inferiority on abnormal vascular structures and failing to distinguish exact coronary arteries from vessel-like structures. In this paper, we propose a context aware 3D fully convolutional network (FCN) for vessel enhancement and segmentation in coronary computed tomography angiography (CTA) volumes. Combining the superior capacity of CNN in extracting discriminative features and satisfactory suppression of vessel-like structures by spatial prior knowledge embedded, the proposed approach significantly outperforms conventional Hessian vesselness based approach on a dataset of 50 coronary CTA volumes.

Please log in to get access to your license.

Log in Register for free

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Business + Economics & Engineering + Technology"

Online-Abonnement

Springer Professional "Business + Economics & Engineering + Technology" gives you access to:

  • more than 102.000 books
  • more than 537 journals

from the following subject areas:

  • Automotive
  • Construction + Real Estate
  • Business IT + Informatics
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Mechanical Engineering + Materials
  • Insurance + Risk


Secure your knowledge advantage now!

inform now

Springer Professional "Engineering + Technology"

Online-Abonnement

Springer Professional "Engineering + Technology" gives you access to:

  • more than 67.000 books
  • more than 390 journals

from the following specialised fileds:

  • Automotive
  • Business IT + Informatics
  • Construction + Real Estate
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Mechanical Engineering + Materials





 

Secure your knowledge advantage now!

inform now

Springer Professional "Business + Economics"

Online-Abonnement

Springer Professional "Business + Economics" gives you access to:

  • more than 67.000 books
  • more than 340 journals

from the following specialised fileds:

  • Construction + Real Estate
  • Business IT + Informatics
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Insurance + Risk



Secure your knowledge advantage now!

inform now
previous chapter Stochastic Model-Based Left Ventricle Segmentation in 3D Echocardiography Using Fractional Brownian Motion
next chapter Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas
Title
Context Aware 3D Fully Convolutional Networks for Coronary Artery Segmentation
Authors
Yongjie Duan
Jianjiang Feng
Jiwen Lu
Jie Zhou
Copyright Year
2019
Book
Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

Print ISBN: 978-3-030-12028-3

Electronic ISBN: 978-3-030-12029-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-12029-0_10
This content is only visible if you are logged in and have the appropriate permissions.
This content is only visible if you are logged in and have the appropriate permissions.

Premium Partner

    Image Credits
    Neuer Inhalt/© ITandMEDIA, Nagarro GmbH/© Nagarro GmbH, AvePoint Deutschland GmbH/© AvePoint Deutschland GmbH, AFB Gemeinnützige GmbH/© AFB Gemeinnützige GmbH, USU GmbH/© USU GmbH, Ferrari electronic AG/© Ferrari electronic AG