Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification
(ندگان)پدیدآور
Lavanya, MKannan, P Muthuنوع مدرک
TextResearch Articles
زبان مدرک
Englishچکیده
Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues. The diagnostic methods available are less than effective for detection of cancer. Therefore an automatic lesion segmentation method with computed tomography (CT) scans has been developed. However it is very difficult to perform automatic identification and segmentation of lung tumours with good accuracy because of the existence of variation in lesions. This paper describes the application of a robust lesion detection and segmentation technique to segment every individual cell from pathological images to extract the essential features. The proposed technique based on the FLICM (Fuzzy Local Information Cluster Means) algorithm used for segmentation, with reduced false positives in detecting lung cancers. The back propagation network used to classify cancer cells is based on computer aided diagnosis (CAD).
کلید واژگان
CADFLICM
Cancer biology
شماره نشریه
12تاریخ نشر
2017-12-011396-09-10
ناشر
West Asia Organization for Cancer Prevention (WAOCP)سازمان پدید آورنده
Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha University, Thandalam, Chennai-602 105, India.Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha University, Thandalam, Chennai-602 105, India.
شاپا
1513-73682476-762X