EE SEminar: Companding algorithm for enabling detection of malignant lesions in HDR CT mandibular images
Speaker: Yuval Tamir
M.Sc. student under the supervision of Hedva Spitzer
Wednesday, December 26th, 2018 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering
Companding algorithm for enabling detection of malignant lesions in HDR CT mandibular images
Abstract
Compressing and expanding (companding) HDR computerized Tomography (CT) images of X-ray to a single window is still a relevant challenge for several body organs, even though different approaches have been examined. Besides the general need for simplification of the window setting method for diagnosis requirements, there are clinical needs for resection of malignant lesions in the mandible, for example. In this kind of organ (mandible) the lesions often exist in both the soft tissue and the bone. A suggested algorithm has to take into account the requirement to expose differently the same range of specific grey levels, which is presented at different body tissues.
We propose an adaptive multi-scale contrast companding (AMCC) algorithm. A contrast appears stronger or weaker according to its own value and according to its context contrast, at the different spatial resolutions. The AMCC algorithm successfully compands, with adaptive set of parameters, a large variety of mandibular CT HDR images and natural images as well. Two collaborating physicians evaluated the tumor boundaries, by the single presentation method in 108 mandibular CT window setting and algorithm output images. They found that 92% of all algorithm output images showed at least the same evaluations as the window method did, while 50% of the algorithm output images even yielded improved evaluations. When the evaluation of each slice was done simultaneously, by using both window setting (bone and soft tissue) and algorithm output images, 93% of the evaluations showed preference for the algorithm’s output images. We suggest here, for the first time, a low-cost method for companding the HDR images and ability to perform resection with optimal boundaries definition of mandibular lesions.
