Lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images

Masato Shimazu; Noboru Niki; Hironobu Ohmatsu; Ryutaro Kakinuma; Kenji Eguchi; Masahiro Kaneko; Noriyuki Moriyama

doi:10.1117/12.310871

24 June 1998 Lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images

Masato Shimazu, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, Kenji Eguchi, Masahiro Kaneko, Noriyuki Moriyama

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310871
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

In this paper, we present a lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images. Purpose of this study is to detect the interval change that exist between time different images of same patient. We employed two methods to detect the interval change. The first method is 3D local template matching method. We tried to detect the movement of blood vessel and other organs by this method. The second method is subtraction method. We tried to detect the new shadow by this method. The subtraction technique is the common method which detects the interval change. If the two images are produced in an identical manner, the subtraction image derived from a pair of thin slice CT with time difference having an uniform zero pixel value except for regions with interval changes. However, the same 3D thoracic images are not obtained. Therefore, we study the method to correct the location between 3D thoracic images with time difference.

Citation Download Citation

Masato Shimazu, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, Kenji Eguchi, Masahiro Kaneko, and Noriyuki Moriyama "Lapse observation algorithm for lung cancer detection using 3D thoracic helical CT images", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310871

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