Generalized dynamic range compression algorithm for visualization of chest CT images
| Autor: | Shoji Hara, Kazuo Shimura, Takefumi Nagata |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Image quality
Computer science business.industry media_common.quotation_subject Chest ct Image processing Visualization parasitic diseases Contrast (vision) Dynamic range compression Computer vision Artificial intelligence Representation (mathematics) business Algorithm media_common Volume (compression) |
| Zdroj: | Medical Imaging: Image-Guided Procedures |
| ISSN: | 0277-786X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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