Algorithm:Utah2

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Overview of Utah 2 Algorithms (PI: Guido Gerig)

At Utah, we are interested in a range of algorithms and solutions for the analysis of DTI and the segmentation of healthy brains and brains with lupus lesions from structural MRI.

Utah 2 Projects

	Group Analysis of DTI Fiber Tracts Analysis of populations of diffusion images typically requires time-consuming manual segmentation of structures of interest to obtain correspondance for statistics. This project uses non-rigid registration of DTI images to produce a common coordinate system for hypothesis testing of diffusion properties. More... New: Casey B. Goodlett, P. Thomas Fletcher, John H. Gilmore, Guido Gerig. Group Analysis of DTI Fiber Tract Statistics with Application to Neurodevelopment. NeuroImage 45 (1) Supp. 1, 2009. p. S133-S142.
	Lesion Segmentation Quantification, analysis and display of brain pathology such as white matter lesions as observed in MRI is important for diagnosis, monitoring of disease progression, improved understanding of pathological processes and for developing new therapies. More... New: Marcel Prastawa and Guido Gerig. Automatic MS Lesion Segmentation by Outlier Detection and Information Theoretic Region Partitioning. 3D Segmentation in the Clinic: A Grand Challenge II Workshop at Medical Image Computing and Computer Assisted Intervention (MICCAI) 2008.
	DTI fiber tract statistics Ongoing: As part of this project, we are processing DTI data and computing statistics on fiber tracts. More...
	Influence of Imaging Noise on DTI Statistics Clinical acquisition of diffusion weighted images with high signal to noise ratio remains a challenge. The goal of this project is to understand the impact of MR noise on quantiative statistics of diffusion properties such as anisotropy measures, trace, etc. More...
	Atlas Based Brain Segmentation Automatic segmentation can be performed reliably using priors from brain atlases and an image generative model. We have developed a tool that provides an automatic segmentation pipeline in a modular framework. More...
	Tumor Simulation for Validating Change Tracking Applications Determining extent of pathology as it changes over time is an important clinical task. However, there is a lack of a reliable, objective ground truth for evaluating automatic tracking methods. We have developed a simulation tool that can generate MR images with known tumor and edema. More...
	Evaluation of Registration Algorithms We are interested in comparing existing registration packages to determine how registration in Slicer3 can be improved. This work focuses on examining various packages researchers are currently using for registration and comparing results on a set of examples representative of common registration tasks. More...
	A Framework for Registration Evaluation and Exploration In response to the difficulties of image registration, we propose an environment where registration applications can be explored, tested, and compared. More...