Improvement of Nuclear Cardiology Images for Ischemic Patients Using Image Processing Techniques

This study was performed Nuclear Medicine Department of Fadil Specialist Center and Elnileen Medical Center in Khartoum for 25 Ischemic heart disease patients associated with CAO. This paper presented an appropriate approach for the robust estimation of noise statistic in nuclear cardiology images. The main objective of this study was to Improve of Nuclear Cardiology Images for Ischemic Patients using Image Processing Techniques. For the Single Photon Emission Computed Tomography machine (SPECT) each imaged had been taken for each single case with guidance of ECG trigger by injected patients with (20 mci) of Tc99m-MIBI, then patient wait for 45 min to 1 hour. The scanned image saved as TIFF format images in computer for reservation of image quality. The data analyzed using MatLab program to enhance the cardiac images and adenosine them. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian Scale Mixture model is presented, which accomplishes nonlinearities from scattering. State of art methods use multi scale filtering of images to reduce the irrelevant part of information, based on generic estimation of noise. In this, paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.