introduction:  image  distortion  is  one  of  the  major  problems  of  magnetic  resonance  imaging  (mri) for use in 3dmri, velocity mri, fmri and radiotherapy treatment planning (rttp). it is  widely known that the most obvious effect of the inhomogenity of the magnetic fields and the  nonlinearity  of  the  gradient  is  the  geometric  distortion  of  mr  tomograms.  in  this  study,  the...

t his paper presents a new feature selection approach for automatically extracting   ms lesions in 3d mr images. presented method is applicable to different types of ms lesions. in this method, t1, t2 and flair images are firstly preprocessed. in the next phase, effective features to extract ms lesions are selected by using a genetic algorithm. the fitness function of the genetic algorithm is t...

Background: Surgery and accurate removal of the brain tumor in the operating room and after opening the scalp is one of the major challenges for neurosurgeons due to the removal of skull pressure and displacement and deformation of the brain tissue. This displacement of the brain changes the location of the tumor relative to the MR image taken preoperatively. Methods: This study, which is done...

Medical image registration plays an important role in clinical diagnosis and therapy planning. This paper proposes an automatic method to register computed tomography (CT) and magnetic resonance (MR) brain images by using first principal directions of feature images. In this method, principal component analysis (PCA) neural network is used to calculate the first principal directions from featur...

Introduction: The present study aims to evaluate the Three-Dimensional Diffusion-Weighted reversed fast imaging with steady state free precession (3D DW-PSIF) sequence with respect to imaging of the peripheral nerves; the tibial, medial, and lateral plantar nerves in the lower extremity, ulnar and median nerve in the upper extremity, sciatic nerve, brachial plexus, and lumbosacral plexus, and a...

MR-only radiotherapy treatment planning requires accurate MR-to-CT synthesis. Current deep learning methods for MR-to-CT synthesis depend on pairwise aligned MR and CT training images of the same patient. However, misalignment between paired images could lead to errors in synthesized CT images. To overcome this, we propose to train a generative adversarial network (GAN) with unpaired MR and CT ...

purpose this study was performed to introduce and evaluate the potential of kinematic magnetic resonance imaging (kmri) using a high-field open-magnet magnetic resonance (mr) system. methods we attempted to perform kmri of healthy volunteers’ lumbar spine and knee in the lateral position and ankle in the supine position utilizing the superconducting, horizontally opened, 1.2 t mr system (oasis,...

conclusions in the case of existence gaussian noise, the results confirm that denoising is not effective on the measurement of t2* value. in the case of image distortion by rician noise, a predictor model is proposed to estimate the original t2* value. the predictor model is used to estimate the t2* value of new patients. the predicted t2* values were in good agreement with the corresponding or...

This paper proposes an efficient segmentation algorithm for magnetic resonance (MR) images of the brain using a neuro-fuzzy algorithm. We apply this algorithm to various MR images, acquired from multiple MR scanners at different times, with varying slice thicknesses and fields of view. The proposed algorithm requires a priori knowledge concerning MR images of the brain. For example, MR images o...

background: mr imaging is one of the best diagnostic modalities in medicine. during an mr imaging examination, three types of field are employed to produce images. various experimental studies have been performed about the effects of each single type of field but only few studies are available on their combination to generate mr imaging. the main objective of this research work is to study the ...