This research is developing quantitative image analysis software tools for detecting and precisely measuring anatomical changes in sequences of 3D medical image data, such as MRI or CT scans taken over time. Accurate structural change detection and identification will improve several medical applications such as the experimental evaluation of drugs and treatments, precise monitoring of disease progression, and early disease diagnosis. The key objective of this research is to develop a practical automated change quantitation system that effectively solves the problems encountered in medical change detection applications: high accuracy and reproducibility requirements, structures of complex 3D shape with possible tissue deformation, varying image resolutions and fields-of-view, and numerous image acquisition protocols. The Phase I research program has demonstrated the feasibility of anatomic change measurement by: l) integrating a demonstration end-to-end system for segmenting, registering, and measuring structural change in a sequence of MR images of the same subject, 2) assessing the performance of our approach through experimentation on controlled imagery; and 3) demonstrating the concept of operations on a specific multiple sclerosis lesion tracking problem. In Phase II we propose to incorporate innovative segmentation techniques combining spatial and intensity information for achieving high fidelity geometric structure definitions; integrating surface and volume registration algorithms for simultaneous robustness and accuracy; and automating all components of the system. Validation testing on controlled imagery and a large MRI database of multiple sclerosis subjects is planned.
We are developing a 3D image analysis tool for quantifying structural changes in MR or CT images taken of the same subjects over time. By developing accurate and robust products whose performance is well- understood, we aim to initially develop end-products that may be directly used by clinical researchers for drug efficacy trials, such as for multiple sclerosis and stroke. Such tools also form the backbone of a commercial service in which disease diagnosis and treatment monitoring tests are performed.
|Wu, Ying; Warfield, Simon K; Tan, I Leng et al. (2006) Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI. Neuroimage 32:1205-15|
|Wei, Xingchang; Guttmann, Charles R G; Warfield, Simon K et al. (2004) Has your patient's multiple sclerosis lesion burden or brain atrophy actually changed? Mult Scler 10:402-6|
|Wei, Xingchang; Warfield, Simon K; Zou, Kelly H et al. (2002) Quantitative analysis of MRI signal abnormalities of brain white matter with high reproducibility and accuracy. J Magn Reson Imaging 15:203-9|