Evaluation of Data and Image Quality in Pinhole SPECT
Multi-pinhole collimators are often used in pre-clinical SPECT systems because they have a better resolution-sensitivity tradeoff than parallel hole collimators when imaging small objects. Most multi-pinhole collimators are designed to allow no or only a limited amount of overlap between the different pinhole projections because the ambiguity introduced by multiplexing pinholes can result in artifacts. The origin of these artifacts is still not fully understood, but previous research has already shown that data incompleteness could be part of the explanation. Therefore, we developed a method to investigate data completeness in multiplexing multi-pinhole systems and showed that a certain activity distribution can be successfully reconstructed when the nonmultiplexed data is complete or when the overlap can be sufficiently de-multiplexed. We validated this method using computer simulated phantom data of different multiplexing systems.
We also studied contrast-to-noise and nonprewhitening matched filter signal-to-noise ratio (NPW-SNR) to compare the image quality in a single pinhole system with multiplexing systems. We found that our method can indeed be used to evaluate data completeness in multiplexing systems and found no artifacts in the systems that had complete data. Sensitivity increased significantly with multiplexing but we found only small, nonsignificant differences in contrast-to-noise ratio. However, the NPW-SNR did slightly improve in the multiplexing setups. We conclude that more multiplexing does not necessarily result in more artifacts and that even a high amount of multiplexing can still result in artifact-free images if the nonmultiplexed data is complete or when the overlap can be sufficiently de-multiplexed.
Related Matlab Project Titles:
- Vertebroplasty Performance on Simulator for 19 Surgeons Using Hierarchical Task Analysis.
- Multi-Dimensional Flow-Preserving Compressed Sensing (MuFloCoS) for Time-Resolved Velocity-Encoded Phase Contrast MRI.
- Regularization Designs for Uniform Spatial Resolution and Noise Properties in Statistical Image Reconstruction for 3-D X-ray CT.
- Including Signal Intensity Increases the Performance of Blind Source Separation on Brain Imaging Data.
- A Model of Population and Subject (MOPS) Intensities with Application to Multiple Sclerosis Lesion Segmentation.
- Multi-Target Tracking with Time-Varying Clutter Rate and Detection Profile: Application to Time-lapse Cell Microscopy Sequences.
- Transcranial Assessment and Visualization of Acoustic Cavitation: Modeling and Experimental Validation.
- Microstructural characterization of the pia-arachnoid complex using optical coherence tomography.
- Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets.
- Analysis of Laser Speckle Contrast Images Variability Using a Novel Empirical Mode Decomposition: Comparison of Results With Laser Doppler Flowmetry Signals Variability
- Axially Elongated Field-Free Point Data Acquisition in Magnetic Particle Imaging.
- Geodesic atlas-based labeling of anatomical trees: Application and evaluation on airways extracted from CT.
- Fast and Robust Design of Time-Optimal k-Space Trajectories in MRI.
- Fast X-Ray CT Image Reconstruction Using a Linearized Augmented Lagrangian Method With Ordered Subsets.
- Spinal Navigation and Imaging: History, Trends and Future.
- A Pipeline for the Generation of Realistic 3D Synthetic Echocardiographic Sequences: Methodology and Open-access Database.
- Automated 3-D Retinal Layer Segmentation of Macular Optical Coherence Tomography Images With Serous Pigment Epithelial Detachments.
- Fast Parallel MR Image Reconstruction via B1-Based, Adaptive Restart, Iterative Soft Thresholding Algorithms (BARISTA).
- Ultrasound Shear Wave Elasticity Imaging Quantifies Coronary Perfusion Pressure Effect on Cardiac Compliance.
Subscribe Our Youtube Channel
You can Watch all Subjects Matlab & Simulink latest Innovative Project Results
We want to support Uncompromise Matlab service for all your Requirements Our Reseachers and Technical team keep update the technology for all subjects ,We assure We Meet out Your Needs.
- Matlab Research Paper Help
- Matlab assignment help
- Matlab Project Help
- Matlab Homework Help
- Simulink assignment help
- Simulink Project Help
- Simulink Homework Help
- Matlab Research Paper Help
- NS3 Research Paper Help
- Omnet++ Research Paper Help
- Customised Matlab Assignments
- Global Assignment Knowledge
- Best Assignment Writers
- Certified Matlab Trainers
- Experienced Matlab Developers
- Over 400k+ Satisfied Students
- Ontime support
- Best Price Guarantee
- Plagiarism Free Work
- Correct Citations
Expert Matlab services just 1-click
Unlimited support we offer you
For better understanding purpose we provide following Materials for all Kind of Research & Assignment & Homework service.
- Result snapshot
- Video Tutorial
- Instructions Profile
- Sofware Install Guide
- Execution Guidance
- Implement Plan
Matlab projects innovators has laid our steps in all dimension related to math works.Our concern support matlab projects for more than 10 years.Many Research scholars are benefited by our matlab projects service.We are trusted institution who supplies matlab projects for many universities and colleges.
Reasons to choose Matlab Projects .org???
Our Service are widely utilized by Research centers.More than 5000+ Projects & Thesis has been provided by us to Students & Research Scholars. All current mathworks software versions are being updated by us.
Our concern has provided the required solution for all the above mention technical problems required by clients with best Customer Support.
- Novel Idea
- Ontime Delivery
- Best Prices
- Unique Work