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A Novel 4D-CT Sorting Method Based on Combined Mutual Information and Edge Gradient
- Source :
- IEEE Access, Vol 7, Pp 138846-138856 (2019)
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Although mutual information is a general method usually being used to measure the similarity of two images, the robustness is questionable due to the absence of spatial information. The purpose of this study is to develop a feasible sorting technique for 4D-CT. A novel sorting algorithm named mutual information and edge gradient (MIEG), which includes spatial information by combining mutual information with a term based on the edge gradient of the image, was proposed to sort sequential CT images. The edge of image was extracted by calculating the wavelet transform modulus maxima, and the gradient similarity coefficient of the edge image was calculated and used to multiply by mutual information to form the final similarity metric. This sorting technique was validated by comparing the 4D-CTs reconstructed using MIEG and Real-time Position Management system (Varian Medical Systems, Inc., Palo Alto, CA). Tumor motion trajectories derived from 4D-CTs were analyzed in three orthogonal directions. Their correlation coefficients (CC) and differences in tumor motion magnitude (Ds) were determined. In addition, Dice similarity coefficient (DSC) was used to measure how well the tumor volumes segmented from the two 4D datasets overlapped with each other. For all patients, the mean CC values were >0.95 in all directions. The mean Ds were
- Subjects :
- Sorting algorithm
General Computer Science
Iterative reconstruction
030218 nuclear medicine & medical imaging
Correlation
03 medical and health sciences
0302 clinical medicine
Robustness (computer science)
sort
General Materials Science
mutual information
Spatial analysis
Mathematics
business.industry
similarity metric
General Engineering
Wavelet transform
Pattern recognition
Mutual information
4D-CT sorting
030220 oncology & carcinogenesis
wavelet transform modulus maxima
dice similarity coefficient
lcsh:Electrical engineering. Electronics. Nuclear engineering
Artificial intelligence
business
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....0aa60ef61a9d0caa60218434b4575c35