Finding Your Niche: Odbadrakh Tuguldur

Odbadrakh Tuguldur, who goes by “Togo”, is an upperclassman pursuing a Bachelors of Science in chemistry. Born in Mongolia, and hailing from Raleigh, North Carolina, Togo came to WVU when his parents moved to West Virginia. Initially a biology major with plans for medical school, Togo took Dr. Xiaodong Shi’s organic chemistry course and promptly switched to a chemistry track

Automatic Color Segmentation of Images with Application to Detection of Variegated Coloring in Skin Tumors

A description is given of a computer vision system, developed to serve as the front-end of a medical expert system, that automates visual feature identification for skin tumor evaluation. The general approach is to create different software modules that detect the presence or absence of critical features. Image analysis with artificial intelligence (AI) techniques, such as the use of heuristics incorporated into image processing algorithms, is the primary approach. On a broad scale, this research addressed the problem of segmentation of a digital image based on color information. The algorithm that was developed to segment the image strictly on the basis of color information was shown to be a useful aid in the identification of tumor border, ulcer, and other features of interest. As a specific application example, the method was applied to 200 digitized skin tumor images to identify the feature called variegated coloring. Extensive background information is provided, and the development of the algorithm is described

Applying Artificial Intelligence to the Identification of Variegated Coloring in Skin Tumors

The importance of color information for the automatic diagnosis of skin tumors by computer vision is demonstrated. The utility of the relative color concept is proved by the results in identifying variegated coloring. A feature file paradigm is shown to provide an effective methodology for the independent development of software modules for expert system/computer vision research. An automatic induction tool is used effectively to generate rules for identifying variegated coloring. Variegated coloring can be identified at rates as high as 92% when using the automatic induction technique in conjunction with the color segmentation metho

Unsupervised Color Image Segmentation: with Application to Skin Tumor Borders

The images used in this research were digitized from 35mm color photographic slides obtained from a private dermatology practice and from New York University. The authors compared 6 color segmentation methods and their effectiveness as part of an overall border-finding algorithm. The PCT/median cut and adaptive thresholding algorithms provided the lowest average error and show the most promise for further individual algorithm development. Combining the different methods resulted in further improvement in the number of correctly identified tumor borders, and by incorporating additional heuristics in merging the segmented object information, one could potentially further increase the success rate. The algorithm is broad-based and suggests several areas for further research. One possible area of exploration is to incorporate an intelligent decision making process as to the number of colors that should be used for segmentation in the PCT/median cut and adaptive thresholding algorithms. For comparison purposes, the number of colors was kept constant at three in the authors\u27\u27 application. Other areas that can be explored are noise removal and object classification to determine the correct tumor objec

An Overview of Algorithmic Music Composition in the Noteworks Software Platform

Presented at the 16th International Conference on Auditory Display (ICAD2010) on June 9-15, 2010 in Washington, DC.Noteworks is music composition software that re-imagines the way music is created, played, and shared. Users create musical compositions by building networks and interacting with them in real time. Noteworks reduces the learning curve for algorithmic-music composition, such that most individuals with a basic knowledge of computer interaction can create original compositions with limited instruction. Dynamic networks have the potential to play back for hours without repeating. This document will provide a brief summary overview of the GUI

Huntingtin disrupts lipid bilayers in a polyQ-length dependent manner

AbstractHuntington's Disease (HD) is a neurodegenerative disorder that is defined by the accumulation of nanoscale aggregates comprised of the huntingtin (htt) protein. Aggregation is directly caused by an expanded polyglutamine (polyQ) domain in htt, leading to a diverse population of aggregate species, such as oligomers, fibrils, and annular aggregates. Furthermore, the length of this polyQ domain is directly related to onset and severity of disease. The first 17 N-terminal amino acids of htt have been shown to further modulate aggregation. Additionally, these 17 amino acids appear to have lipid binding properties as htt interacts with a variety of membrane-containing structures present in cells, such as organelles, and interactions with these membrane surfaces may further modulate htt aggregation. To investigate the interaction between htt exon1 and lipid bilayers, in situ atomic force microscopy (AFM) was used to directly monitor the aggregation of htt exon1 constructs with varying Q-lengths (35Q, 46Q, 51Q, and myc-53Q) on supported lipid membranes comprised of total brain lipid extract. The exon1 fragments accumulated on the lipid membranes, causing disruption of the membrane, in a polyQ dependent manner. Furthermore, the addition of an N-terminal myc-tag to the htt exon1 fragments impeded the interaction of htt with the bilayer

Intensity-based image registration using multiple distributed agents

Image registration is the process of geometrically aligning images taken from different sensors, viewpoints or instances in time. It plays a key role in the detection of defects or anomalies for automated visual inspection. A multiagent distributed blackboard system has been developed for intensity-based image registration. The images are divided into segments and allocated to agents on separate processors, allowing parallel computation of a similarity metric that measures the degree of likeness between reference and sensed images after the application of a transform. The need for a dedicated control module is removed by coordination of agents via the blackboard. Tests show that additional agents increase speed, provided the communication capacity of the blackboard is not saturated. The success of the approach in achieving registration, despite significant misalignment of the original images, is demonstrated in the detection of manufacturing defects on screen-printed plastic bottles and printed circuit boards