Parametric Image

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

Fast and Reliable Estimation of Multiple Parametric Images Using an Integrated Method for Dynamic SPECT

Abstract: Dynamic single photon emission computed tomography (SPECT) has demonstrated the potential to quantitatively estimate physiological parameters in the brain and the heart. The generalized linear least square (GLLS) method is a well-established method for solving linear compartment models with fast computational speed. However, the high level of noise intrinsic in the SPECT data leads to reliability and instability problems of GLLS for generating parametric images. An integrated method is proposed to restrict the noise in both the temporal and spatial domains to estimate multiple parametric images for dynamic SPECT. This method comprises three steps which are optimum image sampling schedule in the projection space, cluster analysis applied postreconstruction and parametric image generation with GLLS. The simulation and experimental studies for the neuronal nicotine acetylcholine receptor tracer of 5-[123I]-iodo-A-85380 were employed to evaluate the performance of the proposed method. The results of influx rate of K1 and volume of distribution of Vd demonstrated that the integrated method was successful in generating low noise parametric images for high noise SPECT data without enhancing the partial volume effect. Furthermore, the integrated method is computationally efficient for potential clinical applications

Parametric image reconstruction using the discrete cosine transform for optical tomography.

Abstract: It is well known that the inverse problem in optical tomography is highly ill-posed. The image reconstruction process is often unstable and nonunique, because the number of the boundary measurements data is far fewer than the number of the unknown parameters to be reconstructed. To overcome this problem, one can either increase the number of measurement data (e.g., multispectral or multifrequency methods), or reduce the number of unknowns (e.g., using prior structural information from other imaging modalities). We introduce a novel approach for reducing the unknown parameters in the reconstruction process. The discrete cosine transform (DCT), which has long been used in image compression, is here employed to parameterize the reconstructed image. In general, only a few DCT coefficients are needed to describe the main features in an optical tomographic image. Thus, the number of unknowns in the image reconstruction process can be drastically reduced. We show numerical and experimental examples that illustrate the performance of the new algorithm as compared to a standard model-based iterative image reconstructions scheme. We especially focus on the influence of initial guesses and noise levels on the reconstruction results.

Parametric Imaging Of Digital Subtraction Angiography Studies For Renal Transplant Evaluation

Abstract: A noninvasive method for diagnosing acute tubular necrosis and rejection would be an important tool for the management of renal transplant patients. From a sequence of digital subtraction angiographic images acquired after an intravenous injection of radiographic contrast material, the parametric images of the maximum contrast, the time when the maximum contrast is reached, and two times the time at which one half of the maximum contrast is reached are computed. The parametric images of the time when the maximum is reached clearly distinguish normal from abnormal renal function. However, it is the parametric image of two times the time when one half of the maximum is reached which provides some assistance in differentiating acute tubular necrosis from rejection.© (1981) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Relative Patlak plot for dynamic PET parametric imaging without the need for early-time input function.

Abstract: The Patlak graphical method is widely used in parametric imaging for modeling irreversible radiotracer kinetics in dynamic PET. The net influx rate of radiotracer can be determined from the slope of the Patlak plot. The implementation of the standard Patlak method requires the knowledge of full-time input function from the injection time until the scan end time, which presents a challenge for use in the clinic. This paper proposes a new relative Patlak plot method that does not require early-time input function and therefore can be more efficient for parametric imaging. Theoretical analysis proves that the effect of early-time input function is a constant scaling factor on the Patlak slope estimation. Thus, the parametric image of the slope of the relative Patlak plot is related to the parametric image of standard Patlak slope by a global scaling factor. This theoretical finding has been further demonstrated by computer simulation and real patient data. The study indicates that parametric imaging of the relative Patlak slope can be used as a substitute of parametric imaging of standard Patlak slope for tasks that do not require absolute quantification, such as lesion detection and tumor volume segmentation.

Controlling the signal-to-noise ratio in optical parametric image amplification

Abstract: We analyse a scheme for phase-sensitive amplification of an optical image without using Fourier-transforming lenses, as carried out in a recent experiment. Our analysis shows that the scheme works well with a broadband amplifier, which ensures that the output image is a faithful copy of the object. In addition, when the area of the pixel detector is close to the minimum imaging resolution, both a large output signal-to-noise ratio and noiseless amplification can be realized.