Author                                                                                                                              
 


Helen T. Nguyen

Biomedical Engineering

Helen Nguyen became interested in signal and imaging applications for biomedical technology when she became acquainted with Professor Kruggel’s research, and she considers having the opportunity to work with her mentor to be the best part of her undergraduate education. For Helen, the most rewarding parts of her research have been working with computer codes, analyzing MRI data, and interpreting quantitative data to produce meaningful and interesting results. Along with improving her C programming skill, Helen feels that her research has made an important contribution to the field of neurobiology. Helen hopes to attend graduate school, with a focus on bioimaging.triangle.gif (504 bytes)

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Abstract                                                                                                                           
 

Until recently, brain structures could only be quantified post mortem. Now, the detailed human brain anatomy can be revealed in vivo by combining magnetic resonance imaging (MRI), with automated image analysis tools. In this study, a large MRI database was used to find quantitative differences in brain structures due to gender and changes that occur with healthy aging. High resolution T1-weighted MR images were acquired in 502 healthy subjects (age 16–70, 248 females and 254 males). First, images were corrected for scanner-induced artifacts. Next, the intracranial compartment was extracted and segmented into the major compartments, grey and white matter and cerebrospinal fluid. Each brain was separated into 116 regions-of-interest based on the Anatomical Automatic Labeling template. Grey matter (GM) concentrations in all regions of all subjects were calculated. Finally, gender-related differences and age-related changes were determined using linear regression. Highly significant results were found in 16 regions in which the GM concentration differed up to 4% between males and females. A highly significant loss of GM concentration with age was found in 72 regions at a rate up to 0.4% per year. The results of our study can be used as normative data to assess the amount of pathological changes due to brain diseases (e.g., cerebral infarction) or due to pathological aging (e.g., Alzheimer’s disease).triangle.gif (504 bytes)

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Faculty Mentor                                                                                                                
 

Frithjof Ralf Kruggel

Henry Samueli School of Engineering
 

Each human brain is unique, even in its macroscopic structure. Magnetic resonance imaging (MRI) is a non-invasive technique to reveal anatomical structures of organs at a high spatial resolution within minutes. We have analyzed a large database of MR images acquired in a population of healthy normal subjects over a life span of five decades. Thus, we define gender-related differences in brain structure, and changes that occur during adulthood. Helen Nguyen, an undergraduate student in Biomedical Engineering, was fascinated to see how new knowledge in Neurobiology can be distilled by mining large databases. This publication summarizes the results of two years of research in Dr. Kruggel’s lab.triangle.gif (504 bytes)

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