A Three-Dimensional Method for Detection of Pulmonary Nodule

Author

Yang, Liu ; Liu Yang ; Li Wei ; Zhao Dazhe

Author_Institution

Key Lab. of Med. Image Comput. of Minist. of Educ., Northeast Univ., Sheyang, China

fYear

2009

fDate

17-19 Oct. 2009

Firstpage

1

Lastpage

4

Abstract

A pulmonary nodule is relatively round lesion, or area of abnormal tissue located within the lung that can be seen in thoracic CT scans. Because noise and same like disturbance of blood vessels and tracheas, detection of the lung nodule is difficult. A three-dimensional pulmonary nodule detection method for thoracic CT scans is proposed in this paper. First, bounding box method and three-dimensional sphere-enhancement filter for nodule candidate selection are applied to enhance volume of interest (VOI). Then, 3D features of the VOI are extracted to train L the neural network classifier to reduce false positive rate. With this method, we can effectively decrease the noises which are nonsphere and achieve a low false positive rate.

Keywords

blood vessels; computerised tomography; feature extraction; filtering theory; image classification; lung; medical image processing; neural nets; abnormal tissue; blood vessel; bounding box method; false positive rate reduction; feature extraction; lung lesion; neural network classifier; pulmonary nodule detection; thoracic CT scan; three-dimensional sphere-enhancement filter; trachea; Biomedical imaging; Blood vessels; Computed tomography; Filtering theory; Filters; Laboratories; Lungs; Machine learning; Neural networks; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-4132-7

Electronic_ISBN

978-1-4244-4134-1

Type

conf

DOI

10.1109/BMEI.2009.5304870

Filename

5304870