Automated detection of lung tumors in PET/CT images using active contour filter

Atsushi Teramoto; Hayato Adachi; Masakazu Tsujimoto; Hiroshi Fujita; Katsuaki Takahashi; Osamu Yamamuro; Tsuneo Tamaki; Masami Nishio; Toshiki Kobayashi

doi:10.1117/12.2081680

20 March 2015 Automated detection of lung tumors in PET/CT images using active contour filter

Atsushi Teramoto, Hayato Adachi, Masakazu Tsujimoto, Hiroshi Fujita, Katsuaki Takahashi, Osamu Yamamuro, Tsuneo Tamaki, Masami Nishio, Toshiki Kobayashi

Author Affiliations +

Proceedings Volume 9414, Medical Imaging 2015: Computer-Aided Diagnosis; 94142V (2015) https://doi.org/10.1117/12.2081680
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

In a previous study, we developed a hybrid tumor detection method that used both computed tomography (CT) and positron emission tomography (PET) images. However, similar to existing computer-aided detection (CAD) schemes, it was difficult to detect low-contrast lesions that touch to the normal organs such as the chest wall or blood vessels in the lung. In the current study, we proposed a novel lung tumor detection method that uses active contour filters to detect the nodules deemed "difficult" in previous CAD schemes. The proposed scheme detects lung tumors using both CT and PET images. As for the detection in CT images, the massive region was first enhanced using an active contour filter (ACF), which is a type of contrast enhancement filter that has a deformable kernel shape. The kernel shape involves closed curves that are connected by several nodes that move iteratively in order to enclose the massive region. The final output of ACF is the difference between the maximum pixel value on the deformable kernel, and pixel value on the center of the filter kernel. Subsequently, the PET images were binarized to detect the regions of increased uptake. The results were integrated, followed by the false positive reduction using 21 characteristic features and three support vector machines. In the experiment, we evaluated the proposed method using 100 PET/CT images. More than half of nodules missed using previous methods were accurately detected. The results indicate that our method may be useful for the detection of lung tumors using PET/CT images.

Citation Download Citation

Atsushi Teramoto, Hayato Adachi, Masakazu Tsujimoto, Hiroshi Fujita, Katsuaki Takahashi, Osamu Yamamuro, Tsuneo Tamaki, Masami Nishio, and Toshiki Kobayashi "Automated detection of lung tumors in PET/CT images using active contour filter", Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94142V (20 March 2015); https://doi.org/10.1117/12.2081680

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