Parametric image formation using clustering for dynamic cardiac SPECT

Smart Filter for Dynamic Spect Image Reconstruction

We present a new filtering algorithm, the SMART filter (simultaneous multiplicative algebraic reconstruction technique) and provide a convergence result. We test it to solve the inverse problem of reconstructing a dynamic medical image where the signal strength changes substantially over the time required for data acquisition. Our test choice is the time-dependent single photon emission compute...

Parametric Distributional Clustering for Image Segmentation

Unsupervised Image Segmentation is one of the central issues in Computer Vision. From the viewpoint of exploratory data analysis, segmentation can be formulated as a clustering problem in which pixels or small image patches are grouped together based on local feature information. In this contribution, parametrical distributional clustering (PDC) is presented as a novel approach to image segment...

SPECT Image Reconstruction Using Compound Prior Models

SPECT images are observation data acquired by a gamma-camera following an orbit around the patient’s body, at regularly spaced angles. A reconstructed image is the discrete representation of a slice or cross-section of the isotope distribution within the patient, transversal to the gamma-camera rotation axis. Bayesian reconstruction methods have been extensively used to reconstruct medical imag...

2006 Image of the Year: Focus on cardiac SPECT/CT.

Filters in 2D and 3D Cardiac SPECT Image Processing

Nuclear cardiac imaging is a noninvasive, sensitive method providing information on cardiac structure and physiology. Single photon emission tomography (SPECT) evaluates myocardial perfusion, viability, and function and is widely used in clinical routine. The quality of the tomographic image is a key for accurate diagnosis. Image filtering, a mathematical processing, compensates for loss of det...