Image segmentation applied to CT examination of lymphangioleiomyomatosis

Jason J. Everhart; T. Michael Cannon; John D. Newell Jr.; David Lynch

doi:10.1117/12.175128

11 May 1994 Image segmentation applied to CT examination of lymphangioleiomyomatosis

Jason J. Everhart, T. Michael Cannon, John D. Newell Jr., David Lynch

Proceedings Volume 2167, Medical Imaging 1994: Image Processing; (1994) https://doi.org/10.1117/12.175128
Event: Medical Imaging 1994, 1994, Newport Beach, CA, United States

Abstract

The purpose of this study is to use modern image segmentation techniques to quantitate cyst area and number within a complete CT examination of the lungs. Lymphangioleiomyomatosis (LAM) was chosen because this disease produces many well defined thin- walled cysts of varying sizes throughout the lungs that provide a good test for 2D image segmentation techniques, which are used to separate LAM cysts from the normal lung tissue. Quantitative measures of the lung, such as cyst area versus frequency, are then automatically extracted. Three women with LAM were examined using CT slices obtained at 20 mm intervals, with 1 to 1.5 mm collimation, and a pixel size of 0.4 - 0.5 mm. Our segmentation algorithm operates in several stages. First, masks for each lung are automatically generated, thus allowing only lung pixels to be considered for the cyst segmentation. Next, we threshold the data under the masks at a level of -900 Hounsfield units. The threshold segments LAM cysts from normal lung tissue and other structures, such as pulmonary veins and arteries. In order to determine the size of individual cysts, we grow all regions having brightness values lower than the threshold within the masked regions. These regions, which correspond to cysts, are then sorted by size, and a cyst histogram for each patient is computed.

Citation Download Citation

Jason J. Everhart, T. Michael Cannon, John D. Newell Jr., and David Lynch "Image segmentation applied to CT examination of lymphangioleiomyomatosis", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175128

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