Lung-Deep: A Computerized Tool for Detection of Lung Nodule Patterns using Deep Learning Algorithms Detection of Lung Nodules Patterns
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 10
Abstract
The detection of lung-related disease for radiologists is a tedious and time-consuming task. For this reason, automatic computer-aided diagnosis (CADs) systems were developed by using digital CT scan images of lungs. The detection of lung nodule patterns is an important step for the automatic development of CAD system. Currently, the patterns of lung nodule are detected through domain-expert knowledge of image processing and accuracy is also not up-to-the-mark. Therefore, a computerized CADs tool is presented in this paper to identify six different patterns of lung nodules based on multi-layer deep learning ( known as Lung-Deep) algorithms compare to state-of-the-art systems without using the technical image processing methods. A multilayer combination of the convolutional neural network (CNN), recurrent neural networks (RNNs) and softmax linear classifiers are integrated to develop the Lung-Deep without doing any pre- or post-processing steps. The Lung-Deep system is tested with manually draw radiologist contours on the 1200 images including 3250 nodules by using statistical measures. On this dataset, the higher sensitivity (SE) of 88%, specificity (SP) of 80% and 0.98 of the area under the receiver operating curve (AUC) of 0.98 are obtained compared to other systems. Hence, this proposed lung-deep system is outperformed by integrating different layers of deep learning algorithms to detect six patterns of nodules.
Authors and Affiliations
Qaisar Abbas
Keywords
Related Articles
- EP ID EP262078
- DOI 10.14569/IJACSA.2017.081015
- Views 102
- Downloads 0
Integration of REST-Based Web Service and Browser Extension for Instagram Spam Detection
In this paper, a REST-based Web Service developed in previous work was integrated with a newly developed browser extension that works in modern browser (Firefox and Google Chrome) using Greasemonkey. It uses previous col...
A Novel Image Encryption Supported by Compression Using Multilevel Wavelet Transform
In this paper we propose a novel approach for image encryption supported by lossy compression using multilevel wavelet transform. We first decompose the input image using multilevel 2-D wavelet transform, and thresholdin...
Finite Element Method Combined with Neural Networks for Power System Grounding Investigation
Even in homogenous soil and for simple geometrical structure the analytical design of a grounding system is a complex and not very accurate procedure. Using Finite Element Analysis (FEA) it can perform a precise design f...
Dependency Test: Portraying Pearson's Correlation Coefficient Targeting Activities in Project Scheduling
In this paper, we discuss project scheduling with conflicting activity-resources. Several project activities require same resources but, may be scheduled with the certain lapse of time resulting in repeatedly using the s...
Evaluation of the Segmentation by Multispectral Fusion Approach with Adaptive Operators : Application to Medical Images
With the development of acquisition image techniques, more and more image data from different sources of image become available. Multi-modality image fusion seeks to combine information from different images to obtain mo...