Active research projects currently use CAP data Complementary radial tagging in assessment of left ventricular function
Our group has recently developed a new MRI tagging sequence that produces radial, rather than cartesian (grid or line) tags. Due to the nature of the radial tag generation process the patient table in the scanner must be moved to an optimal location relative to the isocenter of the magnet in order to obtain the best radial tagging pattern. This table-shift distance is calculated from the centroid of patient's left ventricular blood pool in a short-axis image and the image orientation (normal). We propose to use the CAP database to prospectively determine the percentage of patients for whom an optimal table shift can be accommodated without exceeding the table-shift maximum and gradient linearity. To do so we will manually extract the LV centroid (if the data isn't available in CAP) and automatically extract image orientation information from the DICOM header. These parameters from the CAP database will be used to prospectively estimate the optimum table position for a large patient population.
Investigators:
- Zhe Wang, Daniel B. Ennis, J. Paul Finn (UCLA)
Period: September 2011 - September 2013
Validation of the fast RBF method for nonrigid registration of medical images
The fast Radial Basis Function (RBF) method is particularly aimed at registering different medical image datasets typically used during surgical guidance, where both accuracy and speed of registration are of importance. The method displays subsecond performance and has been successfully tested on the registration of standard-sized data with small to medium discrepancies. The purpose of this validation study is to assess the method on registering datasets which display larger discrepancies hence displaying larger deformations during registration.
Investigators:
- Dr. Rudy Lapeer (PI), Said Khalid Shah (University of East Anglia, UK)
Period: 18 April 2011 - 16 December 2011
Automatic indexation of 4D cardiac images
This project aims to develop and apply new machine learning techniques in cardiac imaging based on shape, motion and appearance markers for efficient image indexation and retrieval from large 4D MR datasets.
Investigators:
- Nicholas Ayache (PI), INRIA
Period: 01 April 2011 - 31 December 2014
Modeling and Analysis of Shape in Cardiac Imaging Data
This project develops new mathematical techniques for direct shape mapping, registration and statistical analyses and provides tools for association of subject phenotypes with shape measures derived as cardiac biomedical imaging markers.
Investigators:
- Ivo Dinov (PI), Yonggang Shi, Arthur Toga (LONI,CCB,UCLA)
Period: April 2011 - 30 June 2011
The Cardiac Atlas Project: Mapping Cardiac Function from Magnetic Resonance Images in the Multi-ethnic Study of Atherosclerosis (MESA) Study
This proposal seeks to quantify the differences in regional heart wall motion in asymptomatic participants in the MESA study, using PCA and ICA analysis of standardized parametric models fitted to the core lab contours.
Investigators:
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Alistair Young (PI), Brett Cowan, Peter Hunter, Pau Medrano-Gracia (Auckland)
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Carissa Fonseca, Kalyanam Shivkumar, Paul Finn (UCLA)
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Joao Lima (Johns Hopkins Medical Center)
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David Bluemke (NIH)
Period: 01 July 2008 - 30 June 2011
The Cardiac Atlas Project: Mapping Cardiac Function from Magnetic Resonance Images in the DETERMINE Study
This proposal seeks to quantify the differences in regional heart wall motion in patients with myocardial infarction in the DETERMINE study, stratified to infarct location, using PCA and ICA analysis of standardized parametric models fitted to the core lab contours.
Investigators:
- Alistair Young (PI), Brett Cowan, Peter Hunter, Pau Medrano-Gracia (Auckland)
Period: 01 July 2008 - 30 June 2011
The Cardiac Atlas Project: Quantification of Regional Wall Motion Differences between DETERMINE and MESA
This proposal seeks to quantify the differences in regional heart wall motion between asymptomatic participants in the MESA study and patients with myocardial infarction in the DETERMINE study, using PCA and ICA analysis of standardized parametric models fitted to the core lab contours.
Investigators:
- Alistair Young (PI), Brett Cowan, Peter Hunter, Pau Medrano-Gracia (Auckland)
- Carissa Fonseca, Kalyanam Shivkumar, Paul Finn (UCLA)
- Joao Lima (Johns Hopkins Medical Center)
- David Bluemke (NIH)
- Daniel Lee, Alan Kadish (Northwestern University)
Period: 01 July 2008 - 30 June 2011