Cone-beam CT (CBCT) is being increasingly used in modern radiation therapy for patient setup and adaptive replanning. However, due to the large volume of x-ray illumination, scatter becomes a rather serious problem and is considered as one of the fundamental limitations of CBCT image quality. Many scatter correction algorithms have been proposed in literature, while a standard practical solutio...

In this paper, we first formalize the problem to be solved, i.e., the Scatter Problem (SP). We then show that SP cannot be deterministically solved. Next, we propose a randomized algorithm for this problem. The proposed solution is trivially self-stabilizing. We then show how to design a self-stabilizing version of any deterministic solution for the Pattern Formation and the Gathering problems....

Fully three-dimensional (3D) positron emission tomography (PET) can achieve high sensitivity of coincidence events, but the absence of inter-slice septa inevitably leads to increased scattered events. The scattered events can represent as much as 50% of the total detected events. In this research, we proposed a scatter correction method for 3D PET based on beam stoppers and dual-energy window a...

PURPOSE This study evaluated the summed measures of macular pigment optical density (MPOD) spatial distribution and their effects on intraocular scatter using a commercially available device (C-Quant, Oculus, USA). METHODS A customized heterochromatic flicker photometer (cHFP) device was used to measure MPOD spatial distribution across the central 16° using a 1° stimulus. MPOD was calculated ...

Chloroplasts regulate their growth to optimize photosynthesis. Quantitative data show that the ratio of total chloroplast area to mesophyll cell area is constant across different cells within a single species and also across species. Wild-type chloroplasts exhibit little scatter around this trend; highly irregularly shaped mutant chloroplasts exhibit more scatter. Here we propose a model motiva...

Scatter plots are mostly used for correlation analysis, but are also a useful tool for understanding the distribution of high-dimensional point cloud data. An important characteristic of such distributions are clusters, and scatter plots have been used successfully to identify clusters in data. Another characteristic of point cloud data that has received less attention so far are regions that c...