Visual Analytics and Segmentation of Color Biomedical High Resolution Cryo-Imaging Scans

Abstract

We describe some observations on the practical implementation of the median cut color quantization algorithm, suitably modified for accurate color rendering. The RGB color space is successively divided in such a way that colors with visual significance, even if relatively small in population, are given representatives in the colormap. Appropriately modified, median cut quantization is nearly as good as our best octree quantization. As with octree quantization, error-diffusion dithering is useful for reducing posterization in large regions with a slow variation in color.

Web‐based imaging viewer for real‐color volumetric reconstruction of human visible project and DICOM datasets

“…For color datasets, the MIP and minIP are based on the conversion of RGB channels into a single grayscale channel. Since voxels are themselves colors for color‐based VR, opacity was assigned to each voxel based on basic color brightness considering the sensitivity of the eye (Gavrilov, Vasiliev, Khramov, Getmanskaya, & Turlapov, 2017; Ghayour & Cantor, 2018).…”