Parametric Image

About: Parametric Image is a research topic. Over the lifetime, 311 publications have been published within this topic receiving 6095 citations.

Fusion of cine magnetic resonance and contrast-enhanced first-pass magnetic resonance data in patients with coronary artery disease: a feasibility study.

Abstract: RATIONALE AND OBJECTIVES The left ventricle (LV) myocardial wall contractibility can be evaluated using cine magnetic resonance imaging (MRI) in a qualitative or quantitative manner. Meanwhile, myocardial perfusion can be assessed using contrast-enhanced first-pass MRI. The authors propose a method of automatically fusing the complementary information from these two cardiac MRI modalities into one single image, from which a match or mismatch between contraction and perfusion could be extracted. METHODS The authors developed a registration algorithm based on the combined use of the global affine transformation and intrinsic landmarks to match images from the same sequence or from two imaging sequences. Contraction and perfusion information was fused by combining a myocardial contour image and a parametric image of the slope of the intensity-time curve, respectively. The fusion paradigm was applied to four patients' data as a demonstration of feasibility of the proposed approach and as a preliminary evaluation. RESULTS Cine MR and contrast-enhanced MR images were well aligned. The contractibility of the LV was displayed by the myocardial contour image. The parametric slope image was consistent with the known coronary artery status of each patient. The combined contraction-perfusion representation of the LV showed the correspondence between regional LV contraction and myocardial perfusion at a one slice level. CONCLUSIONS Left ventricle contraction and myocardial perfusion can be represented conjointly in one single fused image. The fusion paradigm should be evaluated for a larger number of patients to evaluate the clinical relevance of this approach in assessing coronary artery disease.

Image enhancement and dynamic range compression using novel intensity-specific stochastic resonance-based parametric image enhancement model

Abstract: This paper presents a noise-aided image enhancement algorithm focussed on addressing images that have a large dynamic range, i.e., images with both dark and bright regions. The application of a new mathematical model, in a shifted double-well system exhibiting stochastic resonance, is investigated for such images. The new mathematical model addresses the shortcomings of earlier SR-based enhancement model by deriving parameters purely from input values (instead of input statistics). This model is specific to spatial domain pixel representation and operates on a revised iterative equation. This iterative processing is here applied selectively to the under-illuminated regions of the image, characterized as the De Vries-Rose (DVR) region of a human psychovisual model. The idea of suitably modifying the existing universal image quality index is also proposed for its participation in iteration termination, and to gauge the property of dynamic range compression. While the iterative algorithm is terminated using the revised image quality index, entropy maximization, and contrast quality of DVR region with constraints on perceptual quality, the performance of the proposed algorithm is also characterized by observing color enhancement and subjective scores on visual quality.

Pixel-Based Hyperparameter Selection for Feature-Based Image Registration

Abstract: This paper deals with parametric image registration from point correspondences in deformable environments In this problem, it is essential to determine correct values for hyperparameters such as the number of control points of the warp, a smoothing parameter weighting a term in the cost function, or an M-estimator threshold This is usually carried out either manually by a trial-and-error procedure or automatically by optimizing a criterion such as the Cross-Validation score In this paper, we propose a new criterion that makes use of all the available image photometric information We use the point correspondences as a training set to determine the warp parameters and the photometric information as a test set to tune the hyperparameters Our approach is fully robust in the sense that it copes with both erroneous point correspondences and outliers in the images caused by, for instance, occlusions or specularities

Method for tracking of contrast enhancement pattern for pharmacokinetic and parametric analysis in fast-enhancing tissues using high-resolution mri

Abstract: A method for performing a high-resolution pharmacokinetic analysis for calculation of tissue parameters for a fast-enhancing tissue enables medical personal to accuratley determine pharmacokinetic parameters in fast-enhancing tissues (1200). The method includes obtaining mask image data of the tissue when it is in a steady state condition, obtaining a time series of image data of the tissue when the contrast agent is flowing in the tissue, and increasing a spatial resolution (1220) of the time series of image data using the mask image data to obtain a time series of increased spatial resolution image data. The method further includes performing a pharmacokinetic (1230) analysis to obtain data including at least one parameter that characterizes the tissue, providing multiparameter look-up table derived from a combination of two or more parameters, and providing a display including one parameter or a parameteric image, where the parametric image is derived from the look-up table.

Parametric images of antibody pharmacokinetics based on serial quantitative whole-body imaging and blood sampling.

Abstract: We present a method for pharmacokinetic modeling of distributions of In-111-labeled monoclonal antibodies (mAbs) on individual pixels of planar scintillation-camera images. Methods: The method is applied to 2 sets of clinical whole-body images, each consisting of 6 consecutive images acquired over a week. Quantification is performed on a pixel basis, yielding images in units of Bq/pixel. The images acquired on the different occasions are registered using a nonrigid method, and for each pixel location a time-activity curve is obtained for which kinetic modeling is performed. The In-111-mAb is assumed to be located in either the vascular or the extravascular space. The vascular content is assumed to follow the global blood kinetics as determined from blood samples, together with a model parameter alpha that describes the fraction of the whole-body blood volume present in the particular pixel. The rate of change of the extravascular compartment is described by a linear 1-tissue-compartment model with 2 rate constants, K-1' and k(2), reflecting extravasation and washout, respectively. The model is optimized for each pixel position with regard to the values of the 3 parameters (alpha, K-1', and k(2)), resulting in 3 parametric images. From these, images of the cumulated activity in vascular and extravascular spaces are calculated, as is an image of the rate-constants ratio, which is closely related to the volume of distribution. Results: The resulting parametric images are analyzed in terms of the appearance of the time-activity curves at various locations. Results also include interpretation of the parametric images in their clinical context, and the location of regions that exhibit high extravasation and a low washout rate is compared with confirmed malignant sites. Conclusion: Parametric imaging allows the study and analysis of the spatial and temporal distributions of mAbs simultaneously. Parametric imaging enhances regions where the pharmacokinetics differ from the surrounding tissue and provides a tool to detect and locate unexpected kinetic behavior, which is sometimes characteristic of malignant tissue. For dosimetry in radionuclide therapy, parametric imaging offers a less biased means of analyzing serial mAb images than traditional region-of-interest-based analysis. (Less)