Patient-specific coronary blood supply territories for quantitative perfusion analysis.

Myocardial perfusion imaging, coupled with quantitative perfusion analysis, provides an important diagnostic tool for the identification of ischaemic heart disease caused by coronary stenoses. The accurate mapping between coronary anatomy and under-perfused areas of the myocardium is important for diagnosis and treatment. However, in the absence of the actual coronary anatomy during the reporting of perfusion images, areas of ischaemia are allocated to a coronary territory based on a population-derived 17-segment (American Heart Association) AHA model of coronary blood supply.

Investigation into diagnostic accuracy of common strategies for automated perfusion motion correction.

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated.

Fast and robust analysis of dynamic contrast enhanced MRI datasets.

A fully automated method for quantitative analysis of dynamic contrast-enhanced MRI data acquired with low and high field scanners, using spin echo and gradient echo sequences, depicting various joints is presented. The method incorporates efficient pre-processing techniques and a robust algorithm for quantitative assessment of dynamic signal intensity vs. time curves.

Quantitative analysis of dynamic contrast-enhanced MRI datasets of the metacarpophalangeal joints.

Rationale And Objectives: In this article, we propose an alternative approach to voxel-by-voxel analysis, which overcomes problems associated with heuristic methods currently used for dynamic contrast-enhanced MRI (DCE-MRI) data assessment. We aim to allow fully automated extraction of various heuristic parameters via robust preprocessing methods and a new technique for classification of temporal patterns of contrast agent uptake, making full use of all available dynamic frames of the datasets. We also demonstrate that application of efficient preprocessing methods permits more accurate analysis of the dynamic data.

Multispectral classification techniques for terahertz pulsed imaging: an example in histopathology.

Terahertz pulsed imaging is a spectroscopic imaging modality using pulses of electromagnetic radiation (100 GHz-10 THz), and there has been recent interest in studying biomedical specimens. It is usual to display parametric images derived from the measured pulses. In this work, classification was achieved by applying multispectral clustering techniques to sets of parametric images.