فهرست مطالب

Frontiers in Biomedical Technologies - Volume:3 Issue: 1, 2016
  • Volume:3 Issue: 1, 2016
  • تاریخ انتشار: 1395/01/18
  • تعداد عناوین: 5
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  • Atena Akbari, Shahrokh Abbasi-Rad, Amirali Kazeminejad, Hamidreza Saligheh Rad Pages 1-7
    Aging is one of the most important factors affecting cortical bone quality, culminating in cortical bone thinning, increasing the number and size of the pores. As a consequence of these alterations the free water molecules mobility augments and their longitudinal relaxation time (T1) increases. Magnetic resonance imaging with its sensitivity to capture signal from hydrogen proton would be the best candidate to assess the bone quality during aging. By employing an appropriate pulse sequence with short TE (in the range of millisecond) which is capable of acquiring signal from hydrogen molecules of cortical bone pores before decaying, we extracted valuable information of the bone structure. In this feasibility study, five healthy volunteers (3f/2m) were undergone short TE MR imaging with dual-TR technique at 3T in order to calculate cortical bone free water longitudinal relaxation time. The obtained T1 values with the average of 589.32 ± 231.52 ms for cortical bone free water was in a good agreement with literature, and was promising in the sense that STE-MRI has the potential to be used in everyday clinics for cortical bone free water relaxometry.
    Keywords: Cortical Bone, Short Time of Echo (TE), Bone water, Longitudinal Relaxation Time
  • Leila Ghorbanzadeh, Ahmad Esmaili Torshabi Pages 8-19
    Purpose
    In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain’s anatomical structures, for analyzing brain changes, delineating pathological regions, and image-guided interventions. Since manual segmentation is time-consuming and prone to variable sort of errors, which makes automatic techniques more demanding.
    Method
    This paper describes a framework for automatic segmentation of both normal and abnormal anatomy from medical images based on adaptive neuro-fuzzy inference system (ANFIS) which is applicable to different types of tumors. The segmentation framework is comprised of five stages: first, Median filter is applied to remove or reduce the noise of images; second, it is followed by EM clustering to segment it into different parts with variousintensities, to be used for feature extraction in the next step. At the fourth stage, extracted features besides ground truth are used as ANFIS training dataset. Fifth and the last, fordetected abnormal sections either edema or tumor core, level set is adopted for a precise detection of abnormal tissues.
    Results
    This method was applied for 15 High-Grade (HG) and 15 Low-Grade (LG) simulated brain tumor images. Proposed model provided satisfactory outcomes which for the segmentation of whole tumor including both edema and tumor core, Dice index recorded 0.936±0.04 and 0.921±0.02 for HG and LG dataset respectively; however, those of tumor core were 0.899±0/04 and 0.902±0.05 in the mentioned groups.
    Conclusion
    The results of this study prove fuzzy inference systems and neural networks potential applications in clinical image analysis and tumor evaluation for brain cancers.
    A Method for Brain Tumor Delineation Using Adaptive Neuro-Fuzzy Inference System in Combination with Expectation-Maximization Clustering; a Feasibility Study
    Keywords: Automatic Segmentation, EM Clustering, Feature Extraction, ANFIS, Level-Set Evolution
  • Mostafa Kabir, Hamidreza Mashayekhi, Sajjad Aftabi, Hamidreza Khodajou-Chokami Pages 20-27
    In this investigation, after designing an experimental setup, the magnetization parameter of a rectangular bar-shaped permanent magnet has been determined by Magnetic Field Magnitude and Intensity Meter device. For achieving this purpose, after finding the geometrical center of mass of the magnet, by moving Hall-effect sensor in 5mm steps, magnetic flux intensity has been measured by our recently patented device.The accuracy of the experimental values in comparison with available commercial grade and analytical equations demonstrated have confirmed. Our device’s results accuracy has also been approved by benchmarking all results. Following, the magnetization parameter has been extracted using the numerical technique.Results showed very exactly benchmarking and proved the use of this device in measuring the magnetic field in MRI devices. This study will be directed to simulate several subjects like calculating the induced electromotive force (emf).
    Keywords: MFMIM, Magnetization, Magnetic Resonance Imaging(MRI), Experimental measurement, Permanent Magnet
  • Armin Allahverdy, Alireza Khorrami Moghadam, Mohammad Reza Mohammadi, Ali Motie Nasrabadi Pages 28-33
    Purpose
    Attention Deficit Hyperactivity Disorder (ADHD) is the current description of the most prevalent psychiatric disorder of childhood. The essential feature is the developmentally inappropriate degree of inattention, impulsiveness and hyperactivity. Manifestations of ADHD usually appear in most situations, including home, school, work, sporting and social settings.
    Method
    Since the essential feature of ADHD is inattention manner also nonlinear features of EEG may be equivalent to the attention we investigate nonlinear features of the EEG. We evaluated 29 children with AD/HD who were diagnosed by DSM-IV criteria and 20 age-sex matched controls. During recording EEG we showed images to children and asked them to concentrate on those images and number them. Using this method we stimulated visual attention of children.
    Result
    In this study, we use an MLP neural network as a classifier. By investigating these nonlinear features, we obtained a classification with 96.7% accuracy, using frontal lobe electrodes as the best result.
    Conclusion
    Results showed a significant difference between the accuracy of the frontal region, and other regions. This result can confirm the defect in the anterior segment of the brain of ADHD children.
    Keywords: ADHD, Nonlinear Features, EEG, Attention Continuity
  • Sadegh Shurche, Nader Riahialam Pages 34-40
    Purpose
    Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) has been used extensively for the early detection of cerebral ischemia. Tissue-equivalent diffusivity phantoms can play a pivotal role in optimizing the existing imaging protocols used for DW-MRI or when examining the usefulness of novel pulse sequences for DW-MRI.The objective of this work was to build a spherical diffusion phantom which mimics the condition typically found in biological tissues.
    Methods
    To assess the quality control, we prepared Nickel-doped agarose/sucrose gels and to perform a quality control on MRI protocols, we designed a spherical phantom. The quality control protocol was applied on a 3 T clinical MRI system (Siemens) and T1, T2, and ADC maps were generated then calculated the average T1, T2, and ADC values.
    Result
    ADC measurement with Nickel-doped agarose/sucrose using an EPI DW-MRI protocol was very good. The T1, T2 and ADC measurement shows the relaxation and diffusion properties of this phantom is similar to the ones found in biological tissues especially in biological tissues such as fat tissue and air tissue boundaries.
    Conclusion
    Nickel-doped agarose/sucrose gels can be used as reference materials for MRI diffusion measurement. A phantom made of these material can be invaluable in optimizing DW-MRI.
    Keywords: diffusion - weighted MRI_tissue-equivalent diffusivity materials_diffusion phantom_apparent diffusion coefficient