0% Complete
صفحه اصلی
/
سی و سومین کنفرانس بین المللی مهندسی برق
Unveiling Enhanced Image Quality in Sparse-View CT with OSEM- ANLM Algorithm
نویسندگان :
Sayna Jamaati
1
Seyed Abolfazl Hosseini
2
Mohammad Ghorbanzadeh
3
Hossein Arabi
4
1- Sharif university of technology
2- Sharif university of technology
3- Sharif university of technology
4- Geneva University Hospital
کلمات کلیدی :
CT،sparse-view،image reconstruction،OSEM،Asymptotic Non-Local Means
چکیده :
This research presents the Ordered Subset Expectation Maximization-Asymptotic Non-local Means (OSEM-ANLM) algorithm, a novel imaging reconstruction method aimed at improving Computed Tomography (CT) image quality from sparsely sampled data. The algorithm’s performance is evaluated using a patient’s chest CT scan and a brain-skull image from the Rando phantom, with projection views reduced to 60, 45, and 30 to simulate varying data sparsity levels. Comparisons are made against conventional methods, including the Algebraic Reconstruction Technique (ART), OSEM, and OSEM-Non-Local Means(NLM). Qualitative assessments demonstrate the OSEM-ANLM’s superior ability to preserve anatomical structures while minimizing noise and artifacts, even with fewer projection views. Quantitative metrics, including Peak Signal-to-Noise Ratio (PSNR), Normalized Root Mean Square Error (NRMSE), and Structural Similarity Index (SSIM), further validate its effectiveness. For the chest CT image with 30 views (the lowest number of views with the highest level of artifacts), OSEM-ANLM achieves the highest PSNR (38.2693) and SSIM (0.9797), outperforming ART (24.6231, 0.9466), OSEM (25.1310, 0.9512), and OSEM-NLM (36.4061, 0.9669). Similarly, it yields the lowest NRMSE (0.0128), compared to ART (0.0523), OSEM (0.0484), and OSEM-NLM (0.0170). For the brain-skull image, OSEM-ANLM achieves the highest PSNR (37.6986) and SSIM (0.9898), surpassing ART (21.7716, 0.9443), OSEM (23.2124, 0.9521), and OSEM-NLM (35.9652, 0.9833). It also records the lowest NRMSE (0.0160) compared to ART (0.0599), OSEM (0.0526), and OSEM-NLM (0.0279). These results highlight the proposed method’s superior reconstruction accuracy and image fidelity under sparse sampling conditions.
لیست مقالات
لیست مقالات بایگانی شده
Simulation of Two Metal- Semiconductor- Metal Photodetectors for Sensing Power and Angle of Incident Light
Shakila Karami - Maryam Khodadai - Nosrat Granpayeh
تخمین افسردگی مبتنی بر صوت با استفاده از بانک فیلتر و شبکه عصبی ResNet
علی نیک خراسانی - محمدرضا اکبرزاده توتونچی - مجید غیورمبرهن
A Simple Method for Continuous Beam-Steering in SIW based Leaky Wave Antenna
Sina Rezaeeahvanouee - AmirHossein Sadough
Real-Time Stress Detection via Photoplethysmogram Signals: Implementation of a Combined Continuous Wavelet Transform and Convolutional Neural Network on Resource-Constrained Microcontrollers
Yasin Hasanpoor - Amin Rostami - Bahram Tarvirdizadeh - Khalil Alipour - Mohammad Ghamari
طراحی و ساخت تقویت کننده توان اصلاح شده مقاومتی-راکتیوی باند گسترده کلاس B/J با گین بالا در توان خروجی پشتی و شرایط بایاس کلاس AB
سارا آقاجانی - محمود کمره ای - مرضیه چگینی
Design of an Optical Current Transformer for High-Voltage Gas-Insulated Switchgear-Part I: Focus on Optical Sensor Design
Reza Babaei - Asghar Akbari - Arash Moradi
Using Convolutional Neural Networks for Sudden Cardiac Death prediction
Sara Tavazo - Farideh Ebrahimi
یک روش مستقل از پارامترهای خطا بهمنظور تشخیص، دستهبندی و تعیین سکشن خطا در سیستم انتقال چند ترمیناله بر اساس تبدیل موجک گسسته
احسان اکبری - عبدالرضا شیخ الاسلامی
Image quality equations for focused transducer in circular photoacoustic computed tomography
Soheil Hakakzadeh - Zahra Kavehvash
Implementation of a 14-Channel Real-time Compact Data Logger for Structure and Mechanical Engineering Laboratories
Keivan Sadeghinezhad - Esmaeil Najafiaghdam - Sara Dezhakam - Ali Sadeghinezhad
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.4.2