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Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images
Fusion of anatomic information in computed tomography (CT) and functional information in [Formula: see text] positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and C...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690013/ https://www.ncbi.nlm.nih.gov/pubmed/26218993 http://dx.doi.org/10.1120/jacmp.v16i4.5148 |
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author | Yang, Juan Wang, Hongjun Zhang, You Yin, Yong |
author_facet | Yang, Juan Wang, Hongjun Zhang, You Yin, Yong |
author_sort | Yang, Juan |
collection | PubMed |
description | Fusion of anatomic information in computed tomography (CT) and functional information in [Formula: see text] positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined [Formula: see text] PET/CT scanner, the two acquisitions are scanned separately and take a long time, which may induce potential positional errors in global and local caused by respiratory motion or organ peristalsis. So registration (alignment) of whole‐body PET and CT images is a prerequisite for their meaningful fusion. The purpose of this study was to assess the performance of two multimodal registration algorithms for aligning PET and CT images. The proposed gradient of mutual information (GMI)‐based demons algorithm, which incorporated the GMI between two images as an external force to facilitate the alignment, was compared with the point‐wise mutual information (PMI) diffeomorphic‐based demons algorithm whose external force was modified by replacing the image intensity difference in diffeomorphic demons algorithm with the PMI to make it appropriate for multimodal image registration. Eight patients with esophageal cancer(s) were enrolled in this IRB‐approved study. Whole‐body PET and CT images were acquired from a combined [Formula: see text] PET/CT scanner for each patient. The modified Hausdorff distance ([Formula: see text]) was used to evaluate the registration accuracy of the two algorithms. Of all patients, the mean values and standard deviations (SDs) of [Formula: see text] were 6.65 [Formula: see text] voxels and 6.01 [Formula: see text] after the GMI‐based demons and the PMI diffeomorphic‐based demons registration algorithms respectively. Preliminary results on oncological patients showed that the respiratory motion and organ peristalsis in PET/CT esophageal images could not be neglected, although a combined [Formula: see text] PET/CT scanner was used for image acquisition. The PMI diffeomorphic‐based demons algorithm was more accurate than the GMI‐based demons algorithm in registering PET/CT esophageal images. PACS numbers: 87.57.nj, 87.57. Q‐, 87.57.uk |
format | Online Article Text |
id | pubmed-5690013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56900132018-04-02 Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images Yang, Juan Wang, Hongjun Zhang, You Yin, Yong J Appl Clin Med Phys Radiation Oncology Physics Fusion of anatomic information in computed tomography (CT) and functional information in [Formula: see text] positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined [Formula: see text] PET/CT scanner, the two acquisitions are scanned separately and take a long time, which may induce potential positional errors in global and local caused by respiratory motion or organ peristalsis. So registration (alignment) of whole‐body PET and CT images is a prerequisite for their meaningful fusion. The purpose of this study was to assess the performance of two multimodal registration algorithms for aligning PET and CT images. The proposed gradient of mutual information (GMI)‐based demons algorithm, which incorporated the GMI between two images as an external force to facilitate the alignment, was compared with the point‐wise mutual information (PMI) diffeomorphic‐based demons algorithm whose external force was modified by replacing the image intensity difference in diffeomorphic demons algorithm with the PMI to make it appropriate for multimodal image registration. Eight patients with esophageal cancer(s) were enrolled in this IRB‐approved study. Whole‐body PET and CT images were acquired from a combined [Formula: see text] PET/CT scanner for each patient. The modified Hausdorff distance ([Formula: see text]) was used to evaluate the registration accuracy of the two algorithms. Of all patients, the mean values and standard deviations (SDs) of [Formula: see text] were 6.65 [Formula: see text] voxels and 6.01 [Formula: see text] after the GMI‐based demons and the PMI diffeomorphic‐based demons registration algorithms respectively. Preliminary results on oncological patients showed that the respiratory motion and organ peristalsis in PET/CT esophageal images could not be neglected, although a combined [Formula: see text] PET/CT scanner was used for image acquisition. The PMI diffeomorphic‐based demons algorithm was more accurate than the GMI‐based demons algorithm in registering PET/CT esophageal images. PACS numbers: 87.57.nj, 87.57. Q‐, 87.57.uk John Wiley and Sons Inc. 2015-07-08 /pmc/articles/PMC5690013/ /pubmed/26218993 http://dx.doi.org/10.1120/jacmp.v16i4.5148 Text en © 2015 The Authors. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/3.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Yang, Juan Wang, Hongjun Zhang, You Yin, Yong Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title | Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title_full | Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title_fullStr | Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title_full_unstemmed | Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title_short | Evaluation of GMI and PMI diffeomorphic‐based demons algorithms for aligning PET and CT Images |
title_sort | evaluation of gmi and pmi diffeomorphic‐based demons algorithms for aligning pet and ct images |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690013/ https://www.ncbi.nlm.nih.gov/pubmed/26218993 http://dx.doi.org/10.1120/jacmp.v16i4.5148 |
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