Parametric Image

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

Robust fast automatic skull stripping of MRI-T2 data

Abstract: The efficacy of image processing and analysis on skull stripped MR images vis-a-vis the original images is well established. Additionally, compliance with the Health Insurance Portability and Accountability Act (HIPAA) requires neuroimage repositories to anonymise the images before sharing them. This makes the non-trivial skull stripping process all the more significant. While a number of optimal approaches exist to strip the skull from T1-weighted MR images to the best of our knowledge, there is no simple, robust, fast, parameter free and fully automatic technique to perform the same on T2-weighted images. This paper presents a strategy to fill this gap. It employs a fast parameterization of the T2 image intensity onto a standardized T1 intensity scale. The parametric "T1-like" image obtained via the transformation, which takes only a few seconds to compute, is subsequently processed by any of the many T1-based brain extraction techniques to derive the brain mask. Masking the original T2 image with this brain mask strips the skull. By standardizing the intensity of the parametric image, preset algorithm-specific parameters (if any) could be used across multiple datasets. The proposed scheme has been used in a number of phantom and clinical T2 brain datasets to successfully strip the skull.

A Tutorial on Parametric Image Registration

Abstract: 1. Resume This chapter introduces the reader to the area of parametric image registration, from a beginner’s point of view. Given a model, an input image and a reference image, the parametric registration task is to find a set of parameters (of the model) that transform the input image into the reference image. This chapter reviews models of the general projective, affine, similarity and Euclidean transformations of images, and develop a full example for affine and projective transformation. It also describes two new methods of computing the set of image derivatives needed, besides the classical method reported in the literature. The new methods for computing derivatives are faster and more accurate than the classical method.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

Abstract: Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

Computer aided measurement of local myocardial perfusion in MRI

Abstract: Gadolinium-DTPA has been proved to be a safe and adequate contrast agent for MRI studies of ischemic heart disease. An important problem arising in quantitative image sequence analysis is the heart movement, mainly due to respiration. An X window based interactive software package allows one to align the images, to calculate regional perfusion-time curves and parametric images showing the maximal perfusion speed. A typical analysis procedure starts with the computer assisted detection of the outer contours of the heart. Based on the calculation of the centre of gravity of the heart region, alignment is carried out. Several regions of interest can now be selected in order to measure the regional perfusion characteristics. The parametric image, showing the maximal perfusion speed, appears to be particularly useful for delineating regions of reduced perfusion. >

Absolute radiance imaging using parametric image amplification

Abstract: We show that parametric image amplification can be used to achieve a 2D radiance map directly expressed in photons per spatiotemporal mode. Radiance images of incoherent signals with less than one photon per mode (typically 10−2) are resolved.