Computed Tomography Image Coding through Air Filtering in the Wavelet Domain

Abstract

Computed Tomography (CT) devices irradiate a (human) body with controlled amounts of X-ray to produce an image where different substance (lung, tissue, vessels, etc.) can be identified unequivocally. Commonly, CT devices also capture areas that do not belong to the human body. Such areas are referred to as air pixels, and may contain imaging artifacts. The air pixels are irrelevant for the medical diagnostic and provoke an important degradation in coding efficiency. In order to improve coding performance, we propose an air filtering technique based on a thresholding in the wavelet domain. The thresholds are determined through the existing relation between wavelet coefficients and image samples, which can be expressed in terms of a probability function. The proposed scheme filters air pixels in the wavelet domain by removing coefficients that are below a given threshold. The thresholds are estimated for different resolution levels and subbands, obtaining a probability of 70% to correctly filter air pixels. Although the proposed technique introduces an slight distortion in terms of RMSE in the biological area, this distortion is negligible compared with the state-of-the-art HDCS filter. These results suggest that the rate-distortion coding performance of our proposal and HDCS outperform significantly the coding performance of JPEG2000. In addition, Table 1 provides the RMSE of the HDCS and our proposal when compared with the original image, indicating that our proposal introduces much less RMSE distortion.