Introduction: Geometric distortion is a major shortcoming of magnetic resonance imaging (MRI), which has an important influence on the accuracy of volumetric measurements, an important parameter in neurology and oncology. Our goal is to design and construct a new three- dimensional phantom using a 3D printer in order to measure geometric distortion and its reproducibility in...

The purpose was to evaluate and correct the co-registration of diagnostic PET/CT and MRI/MRI images for stereotactic radiosurgery (SRS) using 3D volumetric image registration (3DVIR). The 3DVIR utilizes the homogeneity of color distribution over a volumetric anatomical landmark as the registration criterion with submillimeter accuracy. Fifty-three PET/CT and MRI (T1, T2 and FLAIR) image sets of...

In this paper, an optimized fuzzy logic method for Magnetic Resonance Imaging (MRI) brain images segmentation is presented. The method is a technique based on a modified fuzzy c-means (FCM) clustering algorithm. The FCM algorithm that incorporates spatial information into the membership function is used for clustering, while a conventional FCM algorithm does not fully utilize the spatial inform...

Image segmentation is one of the vital steps in Image processing. It is a challenging task in segmenting MRI(Magnetic Resonance Imaging) images because these images have no linear features. But MRI images provide high quality when compared to any other imaging techniques, so it is best suited for clinical diagnosis, biomedical research, etc. This paper presents a novel approach for segmenting M...

There is a growing interest in using multiresolution noise filters in a variety of medical imaging applications. We review recent wavelet denoising techniques for medical ultrasound and for magnetic resonance images and discuss some of their potential applications in the clinical investigations of the brain. Our goal is to present and evaluate noise suppression methods based on both image proce...

MRI of brain can reveal important abnormalities and brain diseases such as brain tumours if these MRI images can be processed properly by intelligent algorithms. As the MRI images have low contrast and contain noise; it is difficult to precisely separate the region of interest between tumour and normal brain tissues. In this paper, computationally intelligent techniques have been presented to c...

BACKGROUND During the follow-up of patients with chronic liver disease, hypervascular hepatocellular carcinomas (HCCs) can develop either from pre-existing high-risk nodules or by de novo hepatocarcinogenesis. The purpose of this study was to evaluate, by retrospective analysis, the detectability and signal intensity on previous hepatocyte-phase gadolinium ethoxybenzyl diethylenetriamine pentaa...

background: for the purpose of individual clinical target volume assessment in radiotherapy of prostate cancer, mrsi was used as a molecular imaging modality with mri and ct images. materials and methods: the images of 20 prostate cancer patients were used in this study. the mr and mrsi images were registered with ct ones using non-rigid registration technique. the ct based planning (bp), ct/mr...

243  Abstract: Accurate automatic detection and classification of images is very challenging task whether they are medical images or other natural images. This paper presents a hybrid technique for automatic classification of MRI images as well as natural images. The proposed method consists of two stages: feature extraction and classification. In first stage, features are extracted from image...

OBJECTIVE To validate the use of contrast-enhanced (CE) fat-suppressed three-dimensional (3D) fast gradient-recalled acquisition in the steady state with radiofrequency spoiling (FSPGR) magnetic resonance imaging (MRI) for the diagnosis of anterolateral soft tissue impingement of the ankle, as compared to the use of routine ankle MRI. MATERIALS AND METHODS Contrast-enhanced fat-suppressed 3D-...