3D live-wire-based semi-automatic segmentation of medical images

Ghassan Hamarneh; Johnson Yang; Chris McIntosh; Morgan Langille

doi:10.1117/12.596148

29 April 2005 3D live-wire-based semi-automatic segmentation of medical images

Ghassan Hamarneh, Johnson Yang, Chris McIntosh, Morgan Langille

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.596148
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

Segmenting anatomical structures from medical images is usually one of the most important initial steps in many applications, including visualization, computer-aided diagnosis, and morphometric analysis. Manual 2D segmentation suffers from operator variability and is tedious and time-consuming. These disadvantages are accentuated in 3D applications and, the additional requirement of producing intuitive displays to integrate 3D information for the user, makes manual segmentation even less approachable in 3D. Robust, automatic medical image segmentation in 2D to 3D remains an open problem caused particularly by sensitivity to low-level parameters of segmentation algorithms. Semi-automatic techniques present possible balanced solution where automation focuses on low-level computing-intensive tasks that can be hidden from the user, while manual inter- vention captures high-level expert knowledge nontrivial to capture algorithmically. In this paper we present a 3D extension to the 2D semi-automatic live-wire technique. Live-wire based contours generated semi-automatically on a selected set of slices are used as seed points on new unseen slices in different orientations. The seed points are calculated from intersections of user-based live-wire techniques with new slices. Our algorithm includes a step for ordering the live-wire seed points in the new slices, which is essential for subsequent multi-stage optimal path calculation. We present results of automatically detecting contours in new slices in 3D volumes from a variety of medical images.

Citation Download Citation

Ghassan Hamarneh, Johnson Yang, Chris McIntosh, and Morgan Langille "3D live-wire-based semi-automatic segmentation of medical images", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.596148

ACCESS THE FULL ARTICLE

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