Image reconstruction, quantification and standard uptake value

2000 ◽  
pp. 17-32
Author(s):  
H. Herzog ◽  
R. D. Hichwa
Keyword(s):  
Image Reconstruction ◽  
Standard Uptake Value ◽  
Reconstruction Quantification

Criteria and Methods for Reliable Three-Dimensional Image Reconstruction

1974 ◽  
Vol 32 ◽  
pp. 330-331
Author(s):  
R. A. Crowther
Keyword(s):  
Image Reconstruction ◽  
Finite Number ◽  
Density Distribution ◽  
Electron Micrographs ◽  
Mathematical Problem ◽  
Three Dimensional ◽  
Ideal Case ◽  
Dimensional Image ◽  
General Object ◽  
The Ideal

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.

Three dimensional deblurring of transmitted-light brightfield micrographs

1993 ◽  
Vol 51 ◽  
pp. 564-565
Author(s):  
Santosh Bhattacharyya
Keyword(s):  
Image Reconstruction ◽  
Three Dimensional ◽  
Transmitted Light ◽  
Reconstruction Algorithms ◽  
3D Image Reconstruction ◽  
Structural Details ◽  
Spread Function ◽  
Early Testing ◽  
Linearized Model ◽  
Image Reconstruction Algorithms

Three dimensional microscopic structures play an important role in the understanding of various biological and physiological phenomena. Structural details of neurons, such as the density, caliber and volumes of dendrites, are important in understanding physiological and pathological functioning of nervous systems. Even so, many of the widely used stains in biology and neurophysiology are absorbing stains, such as horseradish peroxidase (HRP), and yet most of the iterative, constrained 3D optical image reconstruction research has concentrated on fluorescence microscopy. It is clear that iterative, constrained 3D image reconstruction methodologies are needed for transmitted light brightfield (TLB) imaging as well. One of the difficulties in doing so, in the past, has been in determining the point spread function of the system.We have been developing several variations of iterative, constrained image reconstruction algorithms for TLB imaging. Some of our early testing with one of them was reported previously. These algorithms are based on a linearized model of TLB imaging.

Ordered subset expectation maximization algorithm for image reconstruction applied to zero-flow or low-flow mimicking brain phantom

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S678-S678
Author(s):  
Yasuhiro Akazawa ◽  
Yasuhiro Katsura ◽  
Ryohei Matsuura ◽  
Piao Rishu ◽  
Ansar M D Ashik ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Expectation Maximization ◽  
Expectation Maximization Algorithm ◽  
Low Flow ◽  
Brain Phantom ◽  
Zero Flow

Image reconstruction from noisy digital holograms

1990 ◽  
Vol 137 (5) ◽  
pp. 351 ◽  
Author(s):  
C.P. Mariadassou ◽  
B. Yegnanarayana
Keyword(s):  
Image Reconstruction ◽  
Digital Holograms

18F-Deoxyglucose PET for the staging of oesophageal cancer

2003 ◽  
Vol 42 (03) ◽  
pp. 90-93 ◽  
Author(s):  
N. Döbert ◽  
O. Rieker ◽  
W. Kneist ◽  
St. Mose ◽  
A. Teising ◽  
...  
Keyword(s):  
Oesophageal Cancer ◽  
Squamous Cell ◽  
Distal Part ◽  
Standard Uptake Value ◽  
Squamous Cell Carcinomas ◽  
Tumour Grading ◽  
Positron Emission ◽  
Group A ◽  
The Mean ◽  
Drop Outs

SummaryAim: Evaluation of the influence of histopathologic sub-types and grading of primaries of oesophageal cancer, relative to their size and location, on the uptake of 18F-deoxyglucose (FDG) as measured by positron emission tomography (PET). Methods: 50 consecutive patients were evaluated. There were four drop-outs due to previous surgical and/or chemotherapeutical treatments and thus in 46 patients (28 squamous cell carcinomas and 18 adenocarcinomas) a pretherapeutic PET evalution of the primary including a standard uptake value (SUV) was obtained. In 42 cases data on tumour grading were available also. Results: Squamous cell carcinomas (SCC) were in 7/13/8 cases located in the proximal, medial and distal part of the oesophagus, respectively the grading was Gx in 3, G 2 in 12, G2-3 in 7, and G3 in 6 cases. The SUVmax showed a mean of 6.5 ± 2.8 (range 1.7-13.5). Adenocarcinomas (ACA) were located in the medial oesophagus in two cases and otherwise in its distal parts. Grading was Gx in one, G2 in 4, G2-3 in 3, G3 in 3, G3-4 in 3, and G4 in one case. The mean SUVmax was 5.2 ± 3.2 (range 1-13.6) and this was not significantly different from the SCC. Concerning the tumour grading there was a slight, statistically not relevant trend towards higher SUVmax in more dedifferentiated cancer. Discussion: SCC and ACA of the oesophagus show no relevant differences in the FDG-uptake. While there was a significant variability of tumour uptake in the overall study group, a correlation of SUV and tumour grading was not found.

PEMBELAJARAN SIMULASI PENCITRAAN CT DENGAN MENGGUNAKAN PRINSIP REKONSTRUKSI CITRA DALAM SOFTWARE MATLAB

2015 ◽  
Vol 8 (3) ◽  
pp. 161
Author(s):  
Samuel Gideon
Keyword(s):  
Image Reconstruction ◽  
Ct Imaging ◽  
The Body ◽  
Reconstruction Technique ◽  
Imaging Features ◽  
Back Projection ◽  
Cross Sectional ◽  
Low Contrast ◽  
Image Reconstruction Technique ◽  
Imaging Algorithms

This research was conducted as a learning alternatives for study of CT (computed tomograpghy) imaging using image reconstruction technique which are inversion matrix, back projection and filtered back projection. CT imaging can produce images of objects that do not overlap. Objects more easily distinguishable although given the relatively low contrast. The image is generated on CT imaging is the result of reconstruction of the original object. Matlab allows us to create and write imaging algorithms easily, easy to undersand and gives applied and exciting other imaging features. In this study, an example cross-sectional image recon-struction performed on the body of prostate tumors using. With these methods, medical prac-titioner (such as oncology clinician, radiographer and medical physicist) allows to simulate the reconstruction of CT images which almost resembles the actual CT visualization techniques.Keywords : computed tomography (CT), image reconstruction, Matlab

MICROWAVE IMAGING OF EMBEDDED OBJECT USING AN ENHANCED IMAGE RECONSTRUCTION ALGORITHM

2015 ◽  
Vol 74 (20) ◽  
pp. 1793-1801
Author(s):  
Sidi Mohammed Chouiti ◽  
Lotfi Merad ◽  
Sidi Mohammed Meriah ◽  
Xavier Raimundo
Keyword(s):  
Image Reconstruction ◽  
Reconstruction Algorithm ◽  
Microwave Imaging ◽  
Image Reconstruction Algorithm
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