Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach
Background: The evolution of medical imaging plays a vital role in the management of patients with cancer. In oncology, the impact of PET/CT imaging has been contributing widely to the patient treatment by its large advantages over anatomical imaging from screening to staging. PET images provide the...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter Open
2009
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| Online Access: | http://psasir.upm.edu.my/id/eprint/16646/ http://psasir.upm.edu.my/id/eprint/16646/1/Segmenting%20CT%20images%20of%20bronchogenic%20carcinoma%20with%20bone%20metastases%20using%20PET%20intensity%20markers%20approach.pdf |
| _version_ | 1848843019342577664 |
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| author | Avazpour, Iman Roslan, Ros Ernida Bayat, Peyman Saripan, M. Iqbal Nordin, Abdul Jalil Raja Abdullah, Raja Syamsul Azmir |
| author_facet | Avazpour, Iman Roslan, Ros Ernida Bayat, Peyman Saripan, M. Iqbal Nordin, Abdul Jalil Raja Abdullah, Raja Syamsul Azmir |
| author_sort | Avazpour, Iman |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Background: The evolution of medical imaging plays a vital role in the management of patients with cancer. In oncology, the impact of PET/CT imaging has been contributing widely to the patient treatment by its large advantages over anatomical imaging from screening to staging. PET images provide the functional activity inside the body while CT images demonstrate the anatomical information. Hence, the existence of cancer cells can be recognized in PET image but since the structural location and position cannot be defined on PET images, we need to retrieve the information from CT images. Methods: In this study, we highlight the localization of bronchogenic carcinoma by using high activity points on PET image as references to extract regions of interest on CT image. Once PET and CT images have been registered using cross correlation, coordinates of the candidate points from PET are fed into seeded region growing algorithm to define the boundary of lesion on CT. The region growing process continues until a significant change in bilinear pixel values is reached. Results: The method has been tested over eleven images of a patient having bronchogenic carcinoma with bone metastases. The results show that the mean standard error for over segmented pixels is 33% while for the under segmented pixels is 3.4%. Conclusions: Although very simple in implementation, region growing can result in good precision ROIs. The region growing method highly depends on where the growing process starts. Here, by using the data acquired from other modality, we tried to guide the segmentation process to achieve better segmentation results.
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| first_indexed | 2025-11-15T08:08:22Z |
| format | Article |
| id | upm-16646 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:08:22Z |
| publishDate | 2009 |
| publisher | De Gruyter Open |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-166462016-09-29T08:33:58Z http://psasir.upm.edu.my/id/eprint/16646/ Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach Avazpour, Iman Roslan, Ros Ernida Bayat, Peyman Saripan, M. Iqbal Nordin, Abdul Jalil Raja Abdullah, Raja Syamsul Azmir Background: The evolution of medical imaging plays a vital role in the management of patients with cancer. In oncology, the impact of PET/CT imaging has been contributing widely to the patient treatment by its large advantages over anatomical imaging from screening to staging. PET images provide the functional activity inside the body while CT images demonstrate the anatomical information. Hence, the existence of cancer cells can be recognized in PET image but since the structural location and position cannot be defined on PET images, we need to retrieve the information from CT images. Methods: In this study, we highlight the localization of bronchogenic carcinoma by using high activity points on PET image as references to extract regions of interest on CT image. Once PET and CT images have been registered using cross correlation, coordinates of the candidate points from PET are fed into seeded region growing algorithm to define the boundary of lesion on CT. The region growing process continues until a significant change in bilinear pixel values is reached. Results: The method has been tested over eleven images of a patient having bronchogenic carcinoma with bone metastases. The results show that the mean standard error for over segmented pixels is 33% while for the under segmented pixels is 3.4%. Conclusions: Although very simple in implementation, region growing can result in good precision ROIs. The region growing method highly depends on where the growing process starts. Here, by using the data acquired from other modality, we tried to guide the segmentation process to achieve better segmentation results. De Gruyter Open 2009 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/16646/1/Segmenting%20CT%20images%20of%20bronchogenic%20carcinoma%20with%20bone%20metastases%20using%20PET%20intensity%20markers%20approach.pdf Avazpour, Iman and Roslan, Ros Ernida and Bayat, Peyman and Saripan, M. Iqbal and Nordin, Abdul Jalil and Raja Abdullah, Raja Syamsul Azmir (2009) Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach. Radiology and Oncology, 43 (3). pp. 180-186. ISSN 1318-2099; ESSN: 1581-3207 10.2478/v10019-009-0023-y |
| spellingShingle | Avazpour, Iman Roslan, Ros Ernida Bayat, Peyman Saripan, M. Iqbal Nordin, Abdul Jalil Raja Abdullah, Raja Syamsul Azmir Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title | Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title_full | Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title_fullStr | Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title_full_unstemmed | Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title_short | Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach |
| title_sort | segmenting ct images of bronchogenic carcinoma with bone metastases using pet intensity markers approach |
| url | http://psasir.upm.edu.my/id/eprint/16646/ http://psasir.upm.edu.my/id/eprint/16646/ http://psasir.upm.edu.my/id/eprint/16646/1/Segmenting%20CT%20images%20of%20bronchogenic%20carcinoma%20with%20bone%20metastases%20using%20PET%20intensity%20markers%20approach.pdf |