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Change detection in sparse repeat CT scans with non-rigid deformations
Naomi Shamul
,
Leo Joskowicz
*
*
Corresponding author for this work
The Rachel and Selim Benin School of Engineering and Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Scopus citations
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Dive into the research topics of 'Change detection in sparse repeat CT scans with non-rigid deformations'. Together they form a unique fingerprint.
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Keyphrases
Change Detection
100%
Sparse-view
100%
Non-rigid Deformation
100%
Repeat CT Scan
100%
Contrast Change
66%
Non-rigid
66%
Low Contrast
66%
Scanned Image
66%
Space Images
66%
Sinogram
66%
Region of Interest
33%
Computed Tomography
33%
Original Image
33%
Patient Position
33%
Radiologists
33%
Anatomic
33%
Parameter Values
33%
Automatically Identify
33%
Automatic Change Detection
33%
Two-stage Procedure
33%
Error-prone
33%
Prior Image Constrained Compressed Sensing
33%
Region Map
33%
Recall Rate
33%
Compressed Sensing Reconstruction
33%
Precision Rate
33%
Change Type
33%
Reduced Dose
33%
Spacing Methods
33%
High Contrast
33%
Radon Space
33%
Liver Scan
33%
Likelihood Map
33%
Repeated Scans
33%
Non-rigid Registration
33%
Lung CT
33%
Method Parameters
33%
Follow-up CT Scan
33%
Engineering
Image Space
100%
Scan Image
100%
Compressed Sensing
50%
Region of Interest
50%
Space Method
50%
Radiologist
50%
Computer Science
Changed Region
100%
Compressed Sensing
20%
Parameter Value
20%
Constrained Image
20%
Method Parameter
20%
Precision Rate
20%
Phase Procedure
20%
nonrigid registration
20%
Earth and Planetary Sciences
Change Detection
100%
Experimental Study
50%
Biochemistry, Genetics and Molecular Biology
X-Ray Computed Tomography
100%
Reconstruction
16%
Neuroscience
X-Ray Computed Tomography
100%