Development of Efficient Dynamic Magnetic Resonance Imaging Methods with Application to Breast Cancer Detection and Diagnosis.
Abstract
The goal of this predoctoral fellowship research project is to improve the temporal and spatial resolutions in dynamic contrast-enhanced magnetic resonance imaging of the breast by optimizing the Reduced-encoding Imaging by Generalized-series Reconstruction (RIGR) method. Specifically, we investigated the use of non-Fourier encoding for collecting the reduced encoding dynamic data sets. The conclusion from our study was that the current SVD encoding method biases the results towards reproducing the known features in the reference image and, therefore, is not appropriate for dynamic imaging applications. For that reason, we continue to acquire the dynamic data using Fourier encoding. Next, we incorporated dynamic information into the basis functions of the generalized-series model used by the RIGR algorithm. The TRIGR method resulted from incorporating information about the dynamic changes into the basis functions. Explicit edge constraints derived from the reference image were then used along with the contrast information from the dynamic data to inject dynamic information into the basis functions for both RIGR and TRIGR. Of these, the TRIGR method works better for contrast-enhanced imaging because the active reference image can be used for the edge extraction step.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1996
- Accession Number
- ADA320354
Entities
People
- Jill M. Hanson
- Paul Lauterbur
Organizations
- University of Illinois Urbana–Champaign