Computer Aided Diagnosis for Pulmonary Nodule on Low-Dose Computed Tomography (LDCT) Using Density Features

Author

Shen, Wei-Chih ; Yu, Yang-Hao ; Chuang, Cheng-Hung

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Asia Univ., Taichung, Taiwan

fYear

2011

fDate

17-19 Aug. 2011

Firstpage

166

Lastpage

169

Abstract

Low dose CT (LDCT) is imperative in pursuing early detection of lung cancer. From October 2008 to September 2010, 25 patients with 31 nodules were found in the health examination and underwent surgical operations at China Medical University Hospital . Of which, the lesions is classified into atypical adenomatous hyperplasia (AAH), bronchioloalveolar carcinoma (BAC), malignant, or benign other than AAH in the pathologic results. In this study, objective and standardized features were defined based on the CT number analysis in order to describe lesions and construct a computer aided diagnosis system. The diagnostic performance of constructed system is 70.97% in the accuracy index.

Keywords

cancer; computerised tomography; lung; medical image processing; object detection; CT number analysis; China Medical University Hospital; LDCT; atypical adenomatous hyperplasia; bronchioloalveolar carcinoma; computer aided diagnosis system; density features; health examination; low-dose computed tomography; lung cancer early detection; malignant; pulmonary nodule; surgical operations; Cancer; Computed tomography; Computers; Entropy; Lesions; Lungs; Computer Aided Diagnosis; Low-Dose Computed Tomography; Pulmonary Nodule;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Graphics, Imaging and Visualization (CGIV), 2011 Eighth International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4577-0981-4

Type

conf

DOI

10.1109/CGIV.2011.42

Filename

6054073