introduction: filtering can greatly affect the quality of clinical images. determining the best filter and the proper degree of smoothing can help to ensure the most accurate diagnosis. methods: forty five patient’s data aquired during brain phantom spect studies were reconstructed using filtered back-projection technique. the ramp, shepp-logan, cosine, hamming, hanning, butterworth, metz and w...

introduction: one of the major problems in the development of nuclear medicine images is the presence of noise. the noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a fourier transform environment. the main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Introduction: One of the major problems in the development of nuclear medicine images is the presence of noise. The noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a Fourier transform environment. The main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Magnetic Resonance (MR) image is a medical image technique required enormous data to be stored and transmitted for high quality diagnostic application. Various algorithms have been proposed to improve the performance of the compression scheme. In this paper we extended the commonly used algorithms to image compression and compared its performance. For an image compression technique, we have lin...

Introduction: Filtering can greatly affect the quality of clinical images. Determining the best filter and the proper degree of smoothing can help to ensure the most accurate diagnosis. Methods: Forty five patient’s data aquired during brain phantom SPECT studies were reconstructed using filtered back-projection technique. The ramp, Shepp-Logan, Cosine, Hamming, Hanning, Butterworth, Metz...

introduction:  the  purpose  of  this  study  is  to  define  the  optimal  parameters  for  the  tomographic  reconstruction procedure in a routine single photon emission tomography. the hoffman brain phantom  is modified to evaluate the reconstruction method. the phantom was imaged in a 3 and 2-dimensional  conformation and the results were compared.   materials  and  methods:  the  2d  phant...

Image fusion has lots of application in real life to furnish a combined form of many oriented objects of different images into single image. Adaptive Fuzzy logic model with local level processing is a controlling tool to model image characteristics accurately and been successfully applied to a large number of image processing applications. In this paper an adaptive fuzzy logic model have been p...

BACKGROUND Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be ...

We propose a Bayesian approach for the super resolution image reconstruction (SRIR) problem using a Markov random field (MRF) for image characterization. SRIR consists in using a set of low-resolution (LR) images from the same scene to generate a high-resolution (HR) estimate of the original object. Using a Bayesian formulation, it is possible to incorporate previously known spatial information...

Introduction:  The  purpose  of  this  study  is  to  define  the  optimal  parameters  for  the  tomographic  reconstruction procedure in a routine single photon emission tomography. The Hoffman brain phantom  is modified to evaluate the reconstruction method. The phantom was imaged in a 3 and 2-dimensional  conformation and the results were compared.   Materials  and  Methods:  The  2D  phant...