NDLI: Assessing the impact of choosing different deformable registration algorithms on cone-beam CT enhancement by histogram matching

Content Provider	Springer Nature : BioMed Central
Author	Kidar, Halima Saadia Azizi, Hacene
Abstract	Background The aim of this work is to assess the impact of using different deformable registration (DR) algorithms on the quality of cone-beam CT (CBCT) correction with histogram matching (HM). Methods and materials Data sets containing planning CT (pCT) and CBCT images for ten patients with prostate cancer were used. Each pCT image was registered to its corresponding CBCT image using one rigid registration algorithm with mutual information similarity metric (RR-MI) and three DR algorithms with normalized correlation coefficient, mutual information and normalized mutual information (DR-NCC, DR-MI and DR-NMI, respectively). Then, the HM was performed between deformed pCT and CBCT in order to correct the distribution of the Hounsfield Units (HU) in CBCT images. Results The visual assessment showed that the absolute difference between corrected CBCT and deformed pCT was reduced after correction with HM except for soft tissue-air and soft-tissue-bone interfaces due to the improper registration. Furthermore, volumes comparison in terms of average HU error showed that using DR-NCC algorithm with HM yielded the lowest error values of about 55.95 ± 10.43 HU compared to DR-MI and DR-NMI for which the errors were 58.60 ± 10.35 and 56.58 ± 10.51 HU, respectively. Tissue class’s comparison by the mean absolute error (MAE) plots confirmed the performance of DR-NCC algorithm to produce corrected CBCT images with lowest values of MAE even in regions where the misalignment is more pronounced. It was also found that the used method had successfully improved the spatial uniformity in the CBCT images by reducing the root mean squared difference (RMSD) between the pCT and CBCT in fat and muscle from 57 and 25 HU to 8HU, respectively. Conclusion The choice of an accurate DR algorithm before performing the HM leads to an accurate correction of CBCT images. The results suggest that applying DR process based on NCC similarity metric reduces significantly the uncertainties in CBCT images and generates images in good agreement with pCT.
Related Links	https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-018-1162-3.pdf
Ending Page	8
Page Count	8
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s13014-018-1162-3
Journal	Radiation Oncology
Issue Number	1
Volume Number	13
Language	English
Publisher	BioMed Central
Publisher Date	2018-11-07
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Radiotherapy Imaging Radiology CBCT images Deformable registration Histogram matching Adaptive radiation therapy
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Oncology
Journal Impact Factor	3.3/2023
5-Year Journal Impact Factor	3.6/2023

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