Computer Engineering Commons^™

A Hierarchical Method Based On Active Shape Models And Directed Hough Transform For Segmentation Of Noisy Biomedical Images; Application In Segmentation Of Pelvic X-Ray Images, Rebecca Smith, Kayvan Najarian, Kevin R. Ward

Computer Science Publications

Background

Traumatic pelvic injuries are often associated with severe, life-threatening hemorrhage, and immediate medical treatment is therefore vital. However, patient prognosis depends heavily on the type, location and severity of the bone fracture, and the complexity of the pelvic structure presents diagnostic challenges. Automated fracture detection from initial patient X-ray images can assist physicians in rapid diagnosis and treatment, and a first and crucial step of such a method is to segment key bone structures within the pelvis; these structures can then be analyzed for specific fracture characteristics. Active Shape Model has been applied for this task in other bone …

Unified Wavelet And Gaussian Filtering For Segmentation Of Ct Images; Application In Segmentation Of Bone In Pelvic Ct Images, Simina Vasilache, Kevin R. Ward, Charles Cockrell, Jonathan Ha, Kayvan Najarian

Computer Science Publications

Background

The analysis of pelvic CT scans is a crucial step for detecting and assessing the severity of Traumatic Pelvic Injuries. Automating the processing of pelvic CT scans could impact decision accuracy, decrease the time for decision making, and reduce health care cost. This paper discusses a method to automate the segmentation of bone from pelvic CT images. Accurate segmentation of bone is very important for developing an automated assisted-decision support system for Traumatic Pelvic Injury diagnosis and treatment.

Methods

The automated method for pelvic CT bone segmentation is a hierarchical approach that combines filtering and histogram equalization, for image …

A Comparative Analysis Of Multi-Level Computer-Assisted Decision Making Systems For Traumatic Injuries, Soo-Yeon Ji, Rebecca Smith, Toan Huynh, Kayvan Najarian

Computer Science Publications

Background

This paper focuses on the creation of a predictive computer-assisted decision making system for traumatic injury using machine learning algorithms. Trauma experts must make several difficult decisions based on a large number of patient attributes, usually in a short period of time. The aim is to compare the existing machine learning methods available for medical informatics, and develop reliable, rule-based computer-assisted decision-making systems that provide recommendations for the course of treatment for new patients, based on previously seen cases in trauma databases. Datasets of traumatic brain injury (TBI) patients are used to train and test the decision making algorithm. …

Brain Mapping And Detection Of Functional Patterns In Fmri Using Wavelet Transform; Application In Detection Of Dyslexia, Soo-Yeon Ji, Kevin R. Ward, Kayvan Najarian

Computer Science Publications

Background

Functional Magnetic Resonance Imaging (fMRI) has been proven to be useful for studying brain functions. However, due to the existence of noise and distortion, mapping between the fMRI signal and the actual neural activity is difficult. Because of the difficulty, differential pattern analysis of fMRI brain images for healthy and diseased cases is regarded as an important research topic. From fMRI scans, increased blood ows can be identified as activated brain regions. Also, based on the multi-sliced images of the volume data, fMRI provides the functional information for detecting and analyzing different parts of the brain.

Methods

In this …

Automated Ventricular Systems Segmentation In Brain Ct Images By Combining Low-Level Segmentation And High-Level Template Matching, Wenan Chen, Rebecca Smith, Soo-Yeon Ji, Kevin R. Ward, Kayvan Najarian

Computer Science Publications

Background

Accurate analysis of CT brain scans is vital for diagnosis and treatment of Traumatic Brain Injuries (TBI). Automatic processing of these CT brain scans could speed up the decision making process, lower the cost of healthcare, and reduce the chance of human error. In this paper, we focus on automatic processing of CT brain images to segment and identify the ventricular systems. The segmentation of ventricles provides quantitative measures on the changes of ventricles in the brain that form vital diagnosis information.

Methods

First all CT slices are aligned by detecting the ideal midlines in all images. The initial …

Whole-Genome Resequencing Of Escherichia Coli K-12 Mg1655 Undergoing Short-Term Laboratory Evolution In Lactate Minimal Media Reveals Flexible Selection Of Adaptive Mutations, Tom M. Conrad, Andrew R. Royce, M. Kenyon Applebee, Christian L. Barrett, Bin Xie, Yuan Gao, Bernhard Ø. Palsson

Computer Science Publications

Background

Short-term laboratory evolution of bacteria followed by genomic sequencing provides insight into the mechanism of adaptive evolution, such as the number of mutations needed for adaptation, genotype-phenotype relationships, and the reproducibility of adaptive outcomes.

Results

In the present study, we describe the genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in …