Lung Nodule Detection in CT Images using Neuro Fuzzy Classifier
Abstract: Automated lung
cancer detection using computer aided diagnosis (CAD) is an important area in
clinical applications. As the manual nodule detection is very time consuming
and costly so computerized systems can be helpful for this purpose. In this
paper, we propose a computerized system for lung nodule detection in CT scan
images. The automated system consists of two stages i.e. lung segmentation and
enhancement, feature extraction and classification. The segmentation process
will result in separating lung tissue from rest of the image, and only the lung
tissues under examination are considered as candidate regions for detecting
malignant nodules in lung portion. A feature vector for possible abnormal
regions is calculated and regions are classified using neuro fuzzy classifier.
It is a fully automatic system that does not require any manual intervention
and experimental results show the validity of our system.
Author: Anam Tariq, M. Usman
Akram
Journal Code: jptkomputergg130055
