IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
A Fast Approach to Segmentation of PET Brain Images for Extraction of Features
Medical Imaging and Informatics
Preventing signal degradation during elastic matching of noisy DCE-MR eye images
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Exploiting HPC resources for the 3D-time series analysis of caries lesion activity
Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond
XSEDE-enabled high-throughput lesion activity assessment
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
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Abstract: Evaluating precisely the temporal variations of lesion volumes is very important for at least three types of practical applications: pharmaceutical trials, decision making for drug treatment or surgery and patient follow-up. The authors present a volumetric analysis technique, combining precise rigid registration of 3D medical images, nonrigid deformation computation and flowfield analysis. Their analysis technique has two outcomes: the detection of evolving lesions and the quantitative measurement of volume variations. The originality of their approach is that no precise segmentation of the lesion is needed but the approximative designation of a region of interest, which can be automatized. They distinguish between tissue transformation (image intensity changes without deformation) and expansion or contraction effects reflecting a change of mass within the tissue; a real lesion being generally the combination of both effects. The method is tested with synthesized 3D image sequences and applied, in a first attempt to quantify in vivo a mass effect, to the analysis of a patient with multiple sclerosis (MS).