0% Complete
صفحه اصلی
/
سی و دومین کنفرانس بین المللی مهندسی برق
Denoising of the Diffusion Tensor Imaging Data Using k-Space Redundancy
نویسندگان :
Khashayar Esmaeilzadeh
1
Farzaneh Keyvanfard
2
Abbas Nasiraei Moghaddam
3
1- دانشگاه صنعتی امیرکبیر
2- دانشگاه خواجه نصیرالدین طوسی
3- دانشگاه صنعتی امیرکبیر
کلمات کلیدی :
diffusion tensor imaging،denoising filter،spatial frequency domain،fractional anisotropy،cartesian filling
چکیده :
Diffusion tensor imaging is a highly capable, yet noise-sensitive method for obtaining the brain's white matter structure. It comprises repeated acquisitions, each weighted by a diffusion gradient in one specific direction. The acquired data, therefore, has a large amount of redundancy that can be used for its efficient denoising. In this paper, we estimated the pattern for areas in the k-space most affected by the directional diffusion gradient. This pattern was then used for filtrating the acquired data for each direction. In particular, the areas minimally affected by diffusion gradients were replaced by the k-space data that was averaged over all directional acquisitions. The central idea for this filtering is the geometrical constraints on the diffusion caused by fiber orientations. This denoising approach was examined through the resulting reconstructed diffusion images as well as consequent fractional anisotropy (FA) maps, in terms of Signal-to-Noise Ratio and Contrast-to-Noise Ratio (CNR) obtained for different subsampling levels. The results demonstrated a 25.58% increase in SNR and a 27.86% increase in CNR for the FA map when our filter was applied during subsampling (44.44% of each k-space) in the datasets. Additionally, the qualitative assessment showed our filter resulted in a better representation of tracts in the FA map derived from the fully sampled k-spaces.
لیست مقالات
لیست مقالات بایگانی شده
پیاده سازی و بهبود عملکرد شبکه اینترنت اشیا سلولی بر بستر پروژه منبع باز OAI
سیدمحمدرضا طباطبایی نژاد - حسین خالقی بیزکی - سجاد پورسجادی
Gray Box High-Frequency Modeling of Transformer using Particle Swarm Optimization
Mehdi Shamsodini Lori - Mohammad Hamed Samimi - Jawad Faiz
An Iterative Post-processing Method for Speech Source Separation in Realistic Scenarios
Iman Shahriari - Hossein Zeinali
Multi-Objective Particle Swarm Optimization Of Spiral Antenna for Microwave Imaging Applications
Mehdi Yousefnia - Jaber Allahgholipor - Ataollah Ebrahimzadeh
Ground-based Power Line Sag Measurement by Combining Data from a Smartphone and a Laser Rangefinder
Mohammad Javad Abdollahifard - Reza Bahrami
Mapping Human Grasping to 3-Finger Grippers: A Deep Learning Perspective
Fatemeh Naeinian - Elnaz Balazadeh - Mehdi Tale Masouleh
ارائه چارچوب مدیریت بهینه انرژی و انعطافپذیری برای تجمیعکننده منابع انرژی پراکنده
نیلوفر پورقادری - محمود فتوحی فیروز آباد - معین معینی اقطاعی - میلاد کبیری فر
Study of the interaction between different parameters in the fabrication of paper-based microfluidic devices using the wax printing method
MOHAMMAD DERAKHSHANI - SEYED HOSSEIN TAYEBI - MEHRDAD LOTFI CHOOBBARI - AMIR JAHANSHAHI
Improving Power Grid Operational Resilience During A Tornado Disaster
Mohammadali Nazari - Navid Rezaei - Hassan Bevrani
Stability Analysis of Singular 2-D Positive systems
Mahmoud Zamani - Masoud Shafiee - Iman Zamani
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.8.0