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Segmenting CT images of bronchogenic carcinoma with bone metastases using PET intensity markers approach

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journal contribution
posted on 2009-09-01, 00:00 authored by Iman Avazpour, R E Roslan, P Bayat, M I Saripan, A J Nordin, R S A R Abdullah
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.

History

Journal

Radiology and oncology

Volume

43

Issue

3

Pagination

180 - 186

Publisher

Walter de Gruyter

Location

Berlin, Germany

ISSN

1318-2099

eISSN

1581-3207

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2009, Walter de Gruyter

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