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Full-Text Articles in Engineering
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …
Key Technology And Application Of Digital Twin Modeling For Mri, Shanshan Chen, Hongzhi Wang, Tian Xia
Key Technology And Application Of Digital Twin Modeling For Mri, Shanshan Chen, Hongzhi Wang, Tian Xia
Journal of System Simulation
Abstract: With the accelerating digitalization in education, the construction of digital resources and application platforms has caught increasing attention. The framework of MRI equipment digital twin fivedimensional model is constructed to solve the problems in teaching and training for magnetic resonance imaging (MRI). A modeling and simulation method based on the mechanism model is proposed. The multi-dimensional physical data are obtained to perform digital human modeling, and the virtual acquisition and image reconstruction method is proposed to generate images. The digital twin data are adopted for iterative optimization to implement the whole process of the three-dimensional visual operation including preparation …
Pore Structure And Strength Deterioration Mechanism Of Phase Change Energy Storage Backfill, Ai-Bing Jin, You Ju, Hao Sun, Yi-Qing Zhao, Hai Li, Zhou Zhang, Tong Lu
Pore Structure And Strength Deterioration Mechanism Of Phase Change Energy Storage Backfill, Ai-Bing Jin, You Ju, Hao Sun, Yi-Qing Zhao, Hai Li, Zhou Zhang, Tong Lu
Rock and Soil Mechanics
In order to explore the pore structure characteristics of phase change energy storage backfill and their influence on the strength deterioration of backfill, a composite phase change material was prepared with butyl stearate as the phase change material and expanded perlite as the adsorption medium. Cement and tailings were mixed to prepare backfills with different additive amounts of the composite phase change material. The strength and structure characteristics of the phase change energy storage backfill with different addition amounts were obtained by using the methods of CT (computer tomography) scanning, MRI (magnetic resonance imaging) analysis, and uniaxial compression test, and …
Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap
Mri Based Genomic Analysis Of Glioma Using Three Pathway Deep Convolutionalneural Network For Idh Classification, Sonal Gore, Jayant Jagtap
Turkish Journal of Electrical Engineering and Computer Sciences
As per 2016 updates by World Health Organization (WHO) on cancer disease, gliomas are categorized and further treated based on genomic mutations. The imaging modalities support a complimentary but immediate noninvasive diagnosis of cancer based on genetic mutations. Our aim is to train a deep convolutional neural network for isocitrate dehydrogenase (IDH) genotyping of glioma by auto-extracting the most discriminative features from magnetic resonance imaging (MRI) volumes. MR imaging data of total 217 patients were obtained from The Cancer Imaging Archives (TCIA) of high and low-grade gliomas. A 3-pathway convolutional neural network was trained for IDH classification. The multipath neural …
Muscle Activation Via Mri: Comparison Of Techniques, Logan Thorneloe, Neal Bangerter
Muscle Activation Via Mri: Comparison Of Techniques, Logan Thorneloe, Neal Bangerter
Journal of Undergraduate Research
Muscle functional magnetic resonance imaging (mfMRI) is a proven concept to non-invasively identify muscle activation1. Noninvasively identifying muscle activation can be used to diagnose metabolic muscle disease, identify and pinpoint muscular dysfunction, observe muscle deterioration in aging individuals, and help researchers better understand the biological foundation of musclechemistry2. Current proven methods of mfMRI include analyzing pre- and post-exercise T2-weighted images, T2 maps, and sodium images of muscle; however, there is considerable debate around the best of these techniques1-4. We tested these three imaging techniques to determine which has the greatest post-exercise shift in signal intensity.
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Iterative Sensitivity Matrix-Based Magnetic Resonance Conductivity Tensor Imaging, Evren Deği̇rmenci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetic resonance conductivity tensor imaging (MRCTI) reconstructs high-resolution anisotropic conductivity images, which are proved to have critical importance in radio-oncological imaging as well as source localization fields. In the MRCTI technique, linearly independent current injections are applied to the region to be imaged and resulting magnetic flux densities are measured using magnetic resonance imaging techniques. In this study, a novel iterative reconstruction algorithm based on a sensitivity matrix approach is proposed and tested using both simulated and experimental measurements. Obtained results show that the proposed technique can reconstruct anisotropic conductivity images with high and position-independent spatial resolution in addition to …
Decoupling Network For Tx/Rx Body Coil For 7t Mri, Ashraf Abuelhaija, Sana Salamh, Osama Nashwan
Decoupling Network For Tx/Rx Body Coil For 7t Mri, Ashraf Abuelhaija, Sana Salamh, Osama Nashwan
Turkish Journal of Electrical Engineering and Computer Sciences
The parallel imaging technique is widely used in 7T MRI scanners. It employs multichannel RF coil arrays to apply a concurrent excitation and acquisition method. Concurrent excitation faces significant challenges in terms of electromagnetic coupling between the RF coil elements. In order to prevent interference between the RF coil elements' exciters, several decoupling methods have been developed to compensate for coupling and to permit independent work for the exciters. This paper studies the coupling between meander coils arranged in two different geometrical setups and investigates the isolation performance between the coils by applying two different decoupling networks depending on the …
Estimating Left Ventricular Volume With Roi-Based Convolutional Neural Network, Feng Zhu
Estimating Left Ventricular Volume With Roi-Based Convolutional Neural Network, Feng Zhu
Turkish Journal of Electrical Engineering and Computer Sciences
The volume of the human left ventricular (LV) chamber is an important indicator for diagnosing heart disease. Although LV volume can be measured manually with cardiac magnetic resonance imaging (MRI), the process is difficult and time-consuming for experienced cardiologists. This paper presents an end-to-end segmentation-free method that estimates LV volume from MRI images directly. The method initially uses Fourier transform and a regression filter to calculate the region of interest that contains the LV chambers. Then convolutional neural networks are trained to estimate the end-diastolic volume (EDV) and end-systolic volume (ESV). The resulting models accurately estimate the EDV and ESV …
Analysis Of Magnetic Resonance Imaging Of Peripheral Nerve Regeneration, Jaron Lundwall, Alonzo Cook
Analysis Of Magnetic Resonance Imaging Of Peripheral Nerve Regeneration, Jaron Lundwall, Alonzo Cook
Journal of Undergraduate Research
Due to accident-related neural damage, many people’s lives are impaired or limited in what they can do. Current medical practices are limited at helping distal and proximal nerve stubs regenerate. Many recent research studies have focused on trying to improve this problem by understanding how cut or crushed nerves heal. This study focused on helping these efforts by improving non-invasive analysis techniques of nerve growth. Magnetic Resonance Imaging (MRI) is one possible solution to creating a reliable analysis technique that in the future could be used on humans. We have shown that Magnetic Resonance Imaging can be used without invasive …
A New Segmentation Method Of Cerebral Mri Images Based On The Fuzzy C-Means Algorithm, Mohamed Zaki Abderrezak, Mouatez Billah Chibane, Karim Mansour
A New Segmentation Method Of Cerebral Mri Images Based On The Fuzzy C-Means Algorithm, Mohamed Zaki Abderrezak, Mouatez Billah Chibane, Karim Mansour
Turkish Journal of Electrical Engineering and Computer Sciences
The aim of this work is to present a new method for cerebral MRI image segmentation based on modification of the fuzzy c-means (FCM) algorithm. We used local and nonlocal information distance in the initial function of the robust FCM model. The obtained results of the classification of MRI images showed the effectiveness of the suggested model. Calculation of the similarity index confirms that our method is well adapted to MRI images even in the presence of noise.
Mri Image Enhancement Using Biot-Savart Law At 3 Tesla, Yunus Emre Esi̇n, Ferda Nur Alpaslan
Mri Image Enhancement Using Biot-Savart Law At 3 Tesla, Yunus Emre Esi̇n, Ferda Nur Alpaslan
Turkish Journal of Electrical Engineering and Computer Sciences
Coil sensitivity is considered as the most valuable data in the parallel reconstruction of magnetic resonance imaging (MRI). In this study, a novel coil sensitivity map extraction method is introduced for spatially fixed phased array coils. The proposed technique uses the Biot--Savart law with coil internal shape information and low-resolution phase image data to form sensitivity maps. The performance of this method is tested in a parallel image reconstruction task, using the sensitivity-encoding (SENSE) technique. Under the quasi-static assumption and using the duality principle, we computed the sensitivity maps of a phased-array head coil and reconstructed full FOV images. The …
Vessel Segmentation In Mri Using A Variational Image Subtraction Approach, Ayşe Nurdan Saran, Fati̇h Nar, Murat Saran
Vessel Segmentation In Mri Using A Variational Image Subtraction Approach, Ayşe Nurdan Saran, Fati̇h Nar, Murat Saran
Turkish Journal of Electrical Engineering and Computer Sciences
Vessel segmentation is important for many clinical applications, such as the diagnosis of vascular diseases, the planning of surgery, or the monitoring of the progress of disease. Although various approaches have been proposed to segment vessel structures from 3-dimensional medical images, to the best of our knowledge, there has been no known technique that uses magnetic resonance imaging (MRI) as prior information within the vessel segmentation of magnetic resonance angiography (MRA) or magnetic resonance venography (MRV) images. In this study, we propose a novel method that uses MRI images as an atlas, assuming that the patient has an MRI image …