Novel Algorithm for Low-dose CT Image Enhancement Based on Local Feature Analysis
In order to improve the intensity and contrast qualities of CT (Computed Tomography) images in clinic application, this paper proposed a fast and smart low-dose CT images contrast enhancement algorithm based on local feature analysis. The method based on creating active sub-blocks with analyzing the local static feature for each local region. Then, perform a local modified contrast stretching according to an adaptive transfer function within the image region corresponds with the sub-block. The experimental results of two sets CT images with different acquisition protocol (one with 200-250mA tube current, and another with 80mA) show that the proposed algorithm provides a flexible and efficient way for low-dose CT image enhancement, enhances the detail anatomic structure effectively, and constrains the linear artifacts in low-dose CT images preferably than general method. Now, the method is used as a pre-processing procedure in a Lung Cancer CAD system.