Ms. Alena-Kathrin Schnurr Profile

Alena-Kathrin Schnurr

at Ruprecht-Karls-Univ Heidelberg

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 24 March 2016 Paper

Segmentation of hepatic artery in multi-phase liver CT using directional dilation and connectivity analysis

Lei Wang, Alena-Kathrin Schnurr, Stephan Zidowitz, Joachim Georgii, Yue Zhao, Mohammad Razavi, Michael Schwier, Horst Hahn, Christian Hansen

Proceedings Volume 9785, 97851P (2016) https://doi.org/10.1117/12.2217588

KEYWORDS: Image segmentation, Arteries, Liver, Computed tomography, Surgery, Image enhancement, Veins, Image acquisition, Image filtering, Decision support systems, Liver cancer, Expectation maximization algorithms, Photovoltaics

Read Abstract +

Segmentation of hepatic arteries in multi-phase computed tomography (CT) images is indispensable in liver surgery planning. During image acquisition, the hepatic artery is enhanced by the injection of contrast agent. The enhanced signals are often not stably acquired due to non-optimal contrast timing. Other vascular structure, such as hepatic vein or portal vein, can be enhanced as well in the arterial phase, which can adversely affect the segmentation results. Furthermore, the arteries might suffer from partial volume effects due to their small diameter. To overcome these difficulties, we propose a framework for robust hepatic artery segmentation requiring a minimal amount of user interaction. First, an efficient multi-scale Hessian-based vesselness filter is applied on the artery phase CT image, aiming to enhance vessel structures with specified diameter range. Second, the vesselness response is processed using a Bayesian classifier to identify the most probable vessel structures. Considering the vesselness filter normally performs not ideally on the vessel bifurcations or the segments corrupted by noise, two vessel-reconnection techniques are proposed. The first technique uses a directional morphological operator to dilate vessel segments along their centerline directions, attempting to fill the gap between broken vascular segments. The second technique analyzes the connectivity of vessel segments and reconnects disconnected segments and branches. Finally, a 3D vessel tree is reconstructed. The algorithm has been evaluated using 18 CT images of the liver. To quantitatively measure the similarities between segmented and reference vessel trees, the skeleton coverage and mean symmetric distance are calculated to quantify the agreement between reference and segmented vessel skeletons, resulting in an average of 0:55±0:27 and 12:7±7:9 mm (mean standard deviation), respectively.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years