Generalized dynamic range compression algorithm for visualization of chest CT images

Shoji Hara; Kazuo Shimura; Takefumi Nagata

doi:10.1117/12.534676

5 May 2004 Generalized dynamic range compression algorithm for visualization of chest CT images

Shoji Hara, Kazuo Shimura, Takefumi Nagata

Proceedings Volume 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display; (2004) https://doi.org/10.1117/12.534676
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

We formulated a new dynamic range compression (DRC) processing algorithm that can be applied to chest CT images. This new DRC processing algorithm was based on an existing DRC processing algorithm. The new DRC processing algorithm, which we named “Generalized DRC processing,” is categorized as shift variant image processing and can explicitly utilize the results of anatomical region recognition. In addition, the application of the method is not restricted to the DRC. The method can enhance high frequency signals only in the lung due to its shift variant characteristics. Therefore, higher image quality than conventional USM is obtained. When using the Generalized DRC processing for chest CT images, the representation of soft tissues will be improved by roughly recognizing the lung region without affecting the density and contrast of the lung region. Unlike the conventional double gamma method, our method significantly reduces artifacts. In recent years, the reading volume of chest CT images is greatly increasing. In view of this we propose this method, which reduces the number of windowing on a viewer. We believe that this will improve the total reading efficiency, and especially, will allow more efficient lung cancer CT screening.

Citation Download Citation

Shoji Hara, Kazuo Shimura, and Takefumi Nagata "Generalized dynamic range compression algorithm for visualization of chest CT images", Proc. SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, (5 May 2004); https://doi.org/10.1117/12.534676

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