Model and Simulation for Three-dimensional Medical Image Reconstruction of Spiral CT

2008 ◽  
Author(s):  
Feng-rong Sun ◽  
Yan-ling Li ◽  
Ze Liu ◽  
Xiao-hong Qin ◽  
Jun-qing Geng ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Medical Image ◽  
Three Dimensional ◽  
Spiral Ct ◽  
Model And Simulation ◽  
Medical Image Reconstruction

Laser Medical Image Reconstruction and Computer Aided Design of Polymethyl Methacrylate for Pediatric Removable Space Maintainer Applications

2020 ◽  
Vol 10 (12) ◽  
pp. 2842-2848
Author(s):  
Hui Guo ◽  
Yijiao Zhao ◽  
Shawei Feng ◽  
He Liu
Keyword(s):  
Image Reconstruction ◽  
Polymethyl Methacrylate ◽  
Computer Aided Design ◽  
Medical Image ◽  
Three Dimensional ◽  
Conventional Group ◽  
Tissue Surfaces ◽  
Cad Cam ◽  
Medical Image Reconstruction ◽  
The Difference

Background: Although there are many advantages of removable space maintainers (RSM), current methods of making RSM have some limitations. CAD/CAM technology may be used to solve these problems. Methods: Digital model of dentition defects were obtained using scanning technique coupled with laser medical image reconstruction. The digital RSM were designed using 3 shape software. They were manufactured using two methods: Polymethyl methacrylate (PMMA), and conventional methods. The spaces between the tissue surfaces of the RSM and the models were replaced using silicone, the maximum, mean distances and standard deviation were measured. A three-dimensional variation analysis was used to measure these spaces. The variance test compares the difference in distances among various materials. Results: The PMMA RSMs fit the models well. The maximum and mean distances of the PMMA groups were significantly smaller than those of conventional group (p < 0.01). Furthermore, there were no significant different for the standard deviations among PMMA group and the conventional group. Conclusion: Digitally designed and integrated RSMs have good suitability and were better than that of conventional method. PMMA manufactured RSM using CAD/CAM technique may be applied to clinical.

scholarly journals A Web Simulation of Medical Image Reconstruction and Processing as an Educational Tool

2014 ◽  
Vol 28 (1) ◽  
pp. 24-31 ◽  
Author(s):  
Dimitrios Papamichail ◽  
Evaggelos Pantelis ◽  
Panagiotis Papagiannis ◽  
Pantelis Karaiskos ◽  
Evangelos Georgiou
Keyword(s):  
Image Reconstruction ◽  
Medical Image ◽  
Educational Tool ◽  
Medical Image Reconstruction

Research and Developments in Medical Image Reconstruction Methods and Its Applications

2017 ◽  
pp. 491-535
Author(s):  
Shailendra Tiwari ◽  
Rajeev Srivastava
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Medical Imaging ◽  
Medical Image ◽  
Ct Scanner ◽  
Image Reconstruction Techniques ◽  
Reconstruction Methods ◽  
Dimensional Reconstruction ◽  
Development Technology ◽  
Medical Image Reconstruction

Image reconstruction from projection is the field that lays the foundation for Medical Imaging or Medical Image Processing. The rapid and proceeding progress in medical image reconstruction, and the related developments in analysis methods and computer-aided diagnosis, has promoted medical imaging into one of the most important sub-fields in scientific imaging. Computer technology has enabled tomographic and three-dimensional reconstruction of images, illustrating both anatomical features and physiological functioning, free from overlying structures. In this chapter, the authors share their opinions on the research and development in the field of Medical Image Reconstruction Techniques, Computed Tomography (CT), challenges and the impact of future technology developments in CT, Computed Tomography Metrology in industrial research & development, technology, and clinical performance of different CT-scanner generations used for cardiac imaging, such as Electron Beam CT (EBCT), single-slice CT, and Multi-Detector row CT (MDCT) with 4, 16, and 64 simultaneously acquired slices. The authors identify the limitations of current CT-scanners, indicate potential of improvement and discuss alternative system concepts such as CT with area detectors and Dual Source CT (DSCT), recent technology with a focus on generation and detection of X-rays, as well as image reconstruction are discussed. Furthermore, the chapter includes aspects of applications, dose exposure in computed tomography, and a brief overview on special CT developments. Since this chapter gives a review of the major accomplishments and future directions in this field, with emphasis on developments over the past 50 years, the interested reader is referred to recent literature on computed tomography including a detailed discussion of CT technology in the references section.

Learning deconvolutional deep neural network for high resolution medical image reconstruction

2018 ◽  
Vol 468 ◽  
pp. 142-154 ◽  
Author(s):  
Hui Liu ◽  
Jun Xu ◽  
Yan Wu ◽  
Qiang Guo ◽  
Bulat Ibragimov ◽  
...  
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Image Reconstruction ◽  
Medical Image ◽  
Deep Neural Network ◽  
Medical Image Reconstruction
Sign in / Sign up

Export Citation Format

Share Document