A Comparison Between Linear Backprojection (Transpose) And Layergram Backprojection Methods For Image Reconstruciton In Charged–Couple Device (CCD) Based Optical Tomography

2012 ◽  
Author(s):  
Mariani Idroas ◽  
Nora Faaria Sapi’ee ◽  
M.Nasir Ibrahim ◽  
A.Ridhwan Md Zin ◽  
Suhaila M.Najib
Keyword(s):  
Image Reconstruction ◽  
Optical Tomography ◽  
Image Sensor ◽  
Attenuation Coefficients ◽  
Reconstruction Process ◽  
Reconstruction Methods ◽  
Linear Ccd ◽  
Charged Couple Device ◽  
And Inversion ◽  
Ccd Image

Proses pembinaan semula imej untuk tomografi optik berasaskan CCD dengan empat unjuran dibincangkan dalam kertas kerja ini. Deria imej linear CCD yang digunakan dalam projek ini adalah Sony ILX551A yang mempunyai 2048 piksel dengan saiz piksel 14–mikron. Susunan piksel yang digunakan dalam sistem ini adalah gabungan piksel berbentuk oktagon dan segi empat sama untuk memastikan bahawa cahaya merentasi bilangan baris piksel yang sama pada keempat-empat unjuran. Dua kaedah pembinaan semula imej dibincangkan dan dibandingkan dalam kertas kerja ini – kaedah transpose dan kaedah layergram. Kaedah transpose melibatkan pendaraban dan pembalikan matriks manakala kaedah layergram adalah penambahan nilai–nilai attenuation coefficient. Didapati bahawa kaedah layergram menghasilkan imej yang lebih baik daripada kaedah transpose, dari segi kualiti dan kuantiti (nilai α). Namun, kaedah transpose memerlukan masa pemprosesan yang lebih singkat berbanding kaedah layergram. Kata kunci: Optik; tomografi; CCD; pembinaan semula imej The image reconstruction process for CCD–based optical tomography with four projections is discussed in this paper. The CCD linear image sensor used in the study is a Sony ILX551A which has 2048 pixels with a pixel size of 14-microns. The pixel arrangement used in the system is a combination of octagonal and square pixels to ensure that light passes through the same number of pixel rows on all four projections. Two image reconstruction methods are discussed and compared in the paper – the transpose method and the layergram method. The transpose method involves the multiplication and inversion of matrices while the layergram method is simply the addition of the values of attenuation coefficients. The layergram method was found to produce better images than the transpose method, qualitatively and quantitatively (values of α). However, the transpose method requires a shorter processing time than the layergram method. Key words: Optical; tomography; CCD; image reconstruction

scholarly journals Image Reconstruction for Diffuse Optical Tomography Based on Radiative Transfer Equation

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Bo Bi ◽  
Bo Han ◽  
Weimin Han ◽  
Jinping Tang ◽  
Li Li
Keyword(s):  
Image Reconstruction ◽  
Radiative Transfer ◽  
Transfer Equation ◽  
Radiative Transfer Equation ◽  
Optical Tomography ◽  
Measurement Data ◽  
Diffuse Optical Tomography ◽  
Forward Model ◽  
Sparsity Regularization ◽  
Reconstruction Methods

Diffuse optical tomography is a novel molecular imaging technology for small animal studies. Most known reconstruction methods use the diffusion equation (DA) as forward model, although the validation of DA breaks down in certain situations. In this work, we use the radiative transfer equation as forward model which provides an accurate description of the light propagation within biological media and investigate the potential of sparsity constraints in solving the diffuse optical tomography inverse problem. The feasibility of the sparsity reconstruction approach is evaluated by boundary angular-averaged measurement data and internal angular-averaged measurement data. Simulation results demonstrate that in most of the test cases the reconstructions with sparsity regularization are both qualitatively and quantitatively more reliable than those with standardL2regularization. Results also show the competitive performance of the split Bregman algorithm for the DOT image reconstruction with sparsity regularization compared with other existingL1algorithms.

scholarly journals Fingerprint image reconstruction for swipe sensor using Predictive Overlap Method

2018 ◽  
Vol 154 ◽  
pp. 01042
Author(s):  
Ahmad Zafrullah Mardiansyah ◽  
Agus Bejo ◽  
Risanuri Hidayat
Keyword(s):  
Image Reconstruction ◽  
Extraction Process ◽  
Biometric Authentication ◽  
Image Block ◽  
Embedded Devices ◽  
Fingerprint Image ◽  
Reconstruction Process ◽  
Reconstruction Methods ◽  
Extensive Computation ◽  
Overlap Method

Swipe sensor is one of many biometric authentication sensor types that widely applied to embedded devices. The sensor produces an overlap on every pixel block of the image, so the picture requires a reconstruction process before heading to the feature extraction process. Conventional reconstruction methods require extensive computation, causing difficult to apply to embedded devices that have limited computing process. In this paper, image reconstruction is proposed using predictive overlap method, which determines the image block shift from the previous set of change data. The experiments were performed using 36 images generated by a swipe sensor with 128 x 8 pixels size of the area, where each image has an overlap in each block. The results reveal computation can increase up to 86.44% compared with conventional methods, with accuracy decreasing to 0.008% in average.

scholarly journals Survey on Medical Imaging of Electrical Impedance Tomography (EIT) by Variable Current Pattern Methods

2021 ◽  
Vol 2 (2) ◽  
pp. 82-95
Author(s):  
Edriss Eisa Babikir Adam ◽  
Sathesh
Keyword(s):  
Image Reconstruction ◽  
Medical Imaging ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Optical Tomography ◽  
Assessment Process ◽  
Current Direction ◽  
Impedance Tomography ◽  
Research Article ◽  
Reconstruction Methods

Recently, the image reconstruction study on EIT plays a vital role in the medical application field for validation and calibration purpose. This research article analyzes the different types of reconstruction algorithms of EIT in medical imaging applications. Besides, it reviews many methods involved in constructing the electrical impedance tomography. The spatial distribution and resolution with different sensitivity has been discussed here. The electrode arrangement of various methods involved in the EIT system is discussed here. This research article comprises of adjacent drive method, cross method, and alternative opposite current direction method based on the voltage driven pattern. The assessment process of biomedical EIT has been discussed and investigated through the impedance imaging of the existent substances. The locality of the electrodes can be calculated and fixed for appropriate methods. More specifically, this research article discusses about the EIT image reconstruction methods and the significance of the alternative opposite current direction approach in the biomedical system. The change in conductivity test is further investigated based on the injection of current flow in the system. It has been established by the use of Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EDITORS) software, which is open-source software.

Research of Diameter Measurement Based on CCD Image Sensor

2014 ◽  
Vol 602-605 ◽  
pp. 1984-1987
Author(s):  
Ming Quan Yang ◽  
Mei Zhao ◽  
Fei Guo ◽  
Hong Wei Wang
Keyword(s):  
Measurement System ◽  
Direct Contact ◽  
Image Sensor ◽  
Measurement Tool ◽  
Pipe Production ◽  
Diameter Measurement ◽  
Photoelectric Device ◽  
Linear Ccd ◽  
Ccd Image Sensor ◽  
Ccd Image

Use the photoelectric device-linear CCD as a measurement tool, and use the SCM for the data acquisition and data processing, a diameter measurement system which is a low costing, high-precision, non direct contact, can be created. The system can provide diameter real-time monitor to pipe production process.

scholarly journals Investigation of the benefit of PVC in high resolution PET as a post and within reconstruction method for FDG brain data

2020 ◽  
Author(s):  
Evangelos Raptis ◽  
Laura Parkes ◽  
Jose Anton-Rodriguez ◽  
Stephen Carter ◽  
Karl Herholz ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Reconstruction ◽  
Ground Truth ◽  
Image Resolution ◽  
Patient Specific ◽  
Reconstruction Method ◽  
Reconstruction Process ◽  
Reconstruction Methods ◽  
Pet Image Reconstruction ◽  
Anatomical Information

Abstract Purpose: The combination of positron emission tomography (PET) with magnetic resonance imaging (MRI) may enable novel research in the field of dementia. MR data is commonly used in the analysis of PET data for dementia due to its anatomical information and good soft tissue contrast. PET image reconstruction is currently performed independently of MRI data and the images typically suffer from low resolution, poor signal-to-noise ratio and count dependent bias, due to random error in acquired data and the reconstruction process which is ill conditioned. The aim of this research is to investigate the benefit of using anatomical information from MR data within PET image reconstruction, applied to dementia research. Methods: Real PET and MRI patient data of 5 FDG scans of a healthy elderly volunteers, were used in order to create realistic ground truth images of the distribution of matter and activity for these individuals. These ground truth images underwent a Monte-Carlo simulation using SimSET, in order to generate simulated raw data of the high research resolution tomograph (HRRT) PET scanner. The simulations were validated by comparing the reconstructed images to real HRRT data and focusing on image resolution. A comparison of partial volume correction (PVC) of PET data applied within image reconstruction with the conventional approach of applying it post-reconstruction was conducted with typical count levels in order to evaluate the hypothesis that there would be benefit of applying PVC within image reconstruction. Results: Results showed a little improvement in the recovered activity values is seen when using Lucy-Richardson deconvolution both post and within the image reconstruction. Similarly the use of RM modelling showed little benefit. Differences were observed when using Rousset PVC, with larger differences observed when interleaved with reconstruction. Generally the used of Rousset PVC within reconstruction resulted in a decrease in the bias (average error) for large cortical regions, but an increase in bias was observed for small regions and there were apparent region specific and patient specific variations in the observed bias. Conclusions: The benefit of applying PVC as a reconstruction based method showed to be minimal. A region specific bias was observed for most of the reconstruction methods, either applied within or post image reconstruction. Further work is needed to evaluate the benefit of applying PVC methods for high resolution scanners.

A 5732-element linear CCD image sensor

1985 ◽  
Vol 32 (8) ◽  
pp. 1541-1545 ◽  
Author(s):  
L. Yuzuki ◽  
N. Kadekodi ◽  
A. Claproth ◽  
A. Elhatem ◽  
J. Tandon ◽  
...  
Keyword(s):  
Image Sensor ◽  
Linear Ccd ◽  
Ccd Image Sensor ◽  
Ccd Image

Design for Pellet Measurement System Based on TCD1206

2010 ◽  
Vol 40-41 ◽  
pp. 21-26
Author(s):  
Ge Zhu ◽  
Li Na Lou ◽  
Xian Quan Wang ◽  
Jing Luo
Keyword(s):  
Measurement System ◽  
Image Sensor ◽  
Outer Diameter ◽  
Single Chip ◽  
Threshold Method ◽  
Single Chip Microcomputer ◽  
Whole Process ◽  
Linear Ccd ◽  
Ccd Image Sensor ◽  
Ccd Image

The article proposed a kind of new measuring technique suitable for pellet outer diameter --shading of measurement, using high quality laser as the light, linear CCD image sensor TCD1206 acts testing device, TCD1206 produced drive without delay by single-chip microcomputer, process pellet outer diameter signal coming from TCD1206 by floating threshold method of binary, finally the processed binary signals send back to the single-chip microcomputer, through MAX232 serial communication transfer to PC for displaying. The whole process realizes real-time detection to pellet outer diameter, and makes measurement system had higher precision.

scholarly journals POCS-Augmented CycleGAN for MR Image Reconstruction

2021 ◽  
Vol 12 (1) ◽  
pp. 114
Author(s):  
Yiran Li ◽  
Hanlu Yang ◽  
Danfeng Xie ◽  
David Dreizin ◽  
Fuqing Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Magnetic Resonance ◽  
Image Reconstruction ◽  
State Of The Art ◽  
Training Data ◽  
Reconstruction Method ◽  
Mr Image ◽  
Reconstruction Process ◽  
Reconstruction Methods ◽  
Mr Image Reconstruction

Recent years have seen increased research interest in replacing the computationally intensive Magnetic resonance (MR) image reconstruction process with deep neural networks. We claim in this paper that the traditional image reconstruction methods and deep learning (DL) are mutually complementary and can be combined to achieve better image reconstruction quality. To test this hypothesis, a hybrid DL image reconstruction method was proposed by combining a state-of-the-art deep learning network, namely a generative adversarial network with cycle loss (CycleGAN), with a traditional data reconstruction algorithm: Projection Onto Convex Set (POCS). The output of the first iteration’s training results of the CycleGAN was updated by POCS and used as the extra training data for the second training iteration of the CycleGAN. The method was validated using sub-sampled Magnetic resonance imaging data. Compared with other state-of-the-art, DL-based methods (e.g., U-Net, GAN, and RefineGAN) and a traditional method (compressed sensing), our method showed the best reconstruction results.

Sign in / Sign up

Export Citation Format

Share Document