SU-E-J-99: Automated Registration Method Based on Multi-Scale Edge Preserving Scale Space for PET-CT Scanner

2012 ◽  
Vol 39 (6Part7) ◽  
pp. 3675-3675
Author(s):  
Dengwang Li ◽  
H Li ◽  
Y Yin
Keyword(s):  
Scale Space ◽  
Ct Scanner ◽  
Edge Preserving ◽  
Registration Method ◽  
Multi Scale ◽  
Pet Ct ◽  
Automated Registration

Deformable Registration Method Using Edge Preserving Scale Space with Application in Adaptive Radiation Therapy

2012 ◽  
Vol 38 (5) ◽  
pp. 751-758
Author(s):  
Deng-Wang LI ◽  
Hong-Sheng LI ◽  
Hui WANG ◽  
Hong-Jun WANG ◽  
Yong YIN ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Adaptive Radiation ◽  
Scale Space ◽  
Deformable Registration ◽  
Adaptive Radiation Therapy ◽  
Edge Preserving ◽  
Registration Method

Material Identification in Presence of Metal for Baggage Screening

2020 ◽  
Vol 2020 (14) ◽  
pp. 294-1-294-8
Author(s):  
Sandamali Devadithya ◽  
David Castañón
Keyword(s):  
Atomic Number ◽  
Effective Atomic Number ◽  
Simulated Data ◽  
Dual Energy ◽  
Basis Functions ◽  
Total Variation Regularization ◽  
Ct Scanner ◽  
Edge Preserving ◽  
Baggage Screening ◽  
Dual Energy Imaging

Dual-energy imaging has emerged as a superior way to recognize materials in X-ray computed tomography. To estimate material properties such as effective atomic number and density, one often generates images in terms of basis functions. This requires decomposition of the dual-energy sinograms into basis sinograms, and subsequently reconstructing the basis images. However, the presence of metal can distort the reconstructed images. In this paper we investigate how photoelectric and Compton basis functions, and synthesized monochromatic basis (SMB) functions behave in the presence of metal and its effect on estimation of effective atomic number and density. Our results indicate that SMB functions, along with edge-preserving total variation regularization, show promise for improved material estimation in the presence of metal. The results are demonstrated using both simulated data as well as data collected from a dualenergy medical CT scanner.

Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation

2019 ◽  
Vol 12 (3) ◽  
pp. 263-269
Author(s):  
Liu Xian-Hong ◽  
Chen Zhi-Bin
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Filter Bank ◽  
Guided Filter ◽  
Fusion Method ◽  
Edge Preserving ◽  
Directional Information ◽  
Multi Scale ◽  
Directional Filter ◽  
Image Fusion Method

Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

scholarly journals Automatic PET-CT Image Registration Method Based on Mutual Information and Genetic Algorithms

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Martina Marinelli ◽  
Vincenzo Positano ◽  
Francesco Tucci ◽  
Danilo Neglia ◽  
Luigi Landini
Keyword(s):  
Mutual Information ◽  
Optimization Method ◽  
Global Maximum ◽  
Similarity Function ◽  
Spatial Transformation ◽  
Registration Method ◽  
Registration Algorithm ◽  
Positron Emission ◽  
Pet Ct ◽  
Artery Disease

Hybrid PET/CT scanners can simultaneously visualize coronary artery disease as revealed by computed tomography (CT) and myocardial perfusion as measured by positron emission tomography (PET). Manual registration is usually required in clinical practice to compensate spatial mismatch between datasets. In this paper, we present a registration algorithm that is able to automatically align PET/CT cardiac images. The algorithm bases on mutual information (MI) as registration metric and on genetic algorithm as optimization method. A multiresolution approach was used to optimize the processing time. The algorithm was tested on computerized models of volumetric PET/CT cardiac data and on real PET/CT datasets. The proposed automatic registration algorithm smoothes the pattern of the MI and allows it to reach the global maximum of the similarity function. The implemented method also allows the definition of the correct spatial transformation that matches both synthetic and real PET and CT volumetric datasets.

Multiscale registration of medical images based on edge preserving scale space with application in image-guided radiation therapy

2012 ◽  
Vol 57 (16) ◽  
pp. 5187-5204 ◽  
Author(s):  
Dengwang Li ◽  
Hongsheng Li ◽  
Honglin Wan ◽  
Jinhu Chen ◽  
Guanzhong Gong ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Medical Images ◽  
Scale Space ◽  
Edge Preserving ◽  
Image Guided Radiation Therapy ◽  
Image Guided

A combined PET/CT scanner: the path to true image fusion

2002 ◽  
Vol 75 (suppl_9) ◽  
pp. S24-S30 ◽  
Author(s):  
D W Townsend ◽  
T Beyer
Keyword(s):  
Image Fusion ◽  
Ct Scanner ◽  
Pet Ct

Investigation of a Dedicated, High Resolution PET/CT Scanner for Staging and Treatment Planning of Head and Neck Cancer

2015 ◽  
Vol 62 (5) ◽  
pp. 2057-2066
Author(s):  
Raymond R. Raylman ◽  
Alexander V. Stolin ◽  
Prashanth Sompalli ◽  
Nicole Bunda Randall ◽  
Peter F. Martone ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
High Resolution ◽  
Head And Neck ◽  
Treatment Planning ◽  
Neck Cancer ◽  
Ct Scanner ◽  
Pet Ct
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