Logo

Lung nodule detection using multi-resolution analysis

Assefa, Mickias and Faye, Ibrahima and Malik, Aamir Saeed and Shoaib, Muhammad (2013) Lung nodule detection using multi-resolution analysis. In: Proceedings of 2013 ICME International Conference on Complex Medical Engineering, May 25 - 28, 2013, Beijing, China.

[img]
Preview
PDF
457Kb

Official URL: http://dx.doi.org/10.1109/ICCME.2013.6548290

Abstract

The increase in number of smokers in the 20th century leads for lung cancer being the number one killer among cancer related deaths world-wide with an over-all survival rate of only 15%. According to the latest World Health Organization report released on April 2011, Lung cancer is the number one killer among deaths related with cancer for men in Malaysia. In most cases there are no symptoms or warning signs in the early stages of lung cancer. It is often suspected initially from chest x-ray or Computed Tomography (CT) scans done to evaluate a cough or chest pain. Several research work have been aimed at development of Computer Aided Diagnosis (CAD) systems which enhance early detection of lung cancer nodules. This research work aims to develop a CAD system to detect pulmonary lung nodules from Low Dose CT (LDCT) scan images using template matching algorithm integrated with multi-resolution feature analysis technique in order to enhance the false positive detection rate. 134 out of 165 nodules were correctly detected by our scheme. That results in a detection rate of 81.212%.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Pulmonary nodule, template matching Multiresolution Analysis, Computer Aided Diagnosis
Subjects:Q Science > Q Science (General)
R Medicine > R Medicine (General)
T Technology > T Technology (General)
Academic Subject One:Academic Department - Electrical And Electronics - Communications - Digital Communications - Digital Signal Processing
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Mission Oriented Research > Health
ID Code:10967
Deposited By: Dr Aamir Saeed Malik
Deposited On:16 Dec 2013 23:48
Last Modified:16 Dec 2013 23:48

Repository Staff Only: item control page

Document Downloads

More statistics for this item...