Automated Periodontal Diseases Classification System
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 1
Abstract
This paper presents an efficient and innovative system for automated classification of periodontal diseases, The strength of our technique lies in the fact that it incorporates knowledge from the patients' clinical data, along with the features automatically extracted from the Haematoxylin and Eosin (H&E) stained microscopic images. Our system uses image processing techniques based on color deconvolution, morphological operations, and watershed transforms for epithelium & connective tissue segmentation, nuclear segmentation, and extraction of the microscopic immunohistochemical features for the nuclei, dilated blood vessels & collagen fibers. Also, Feedforward Backpropagation Artificial Neural Networks are used for the classification process. We report 100% classification accuracy in correctly identifying the different periodontal diseases observed in our 30 samples dataset
Authors and Affiliations
Aliaa A. A. Youssif , Abeer Saad Gawish , Mohammed Elsaid Moussa
New Hybrid Task Scheduling Algorithm with Fuzzy Logic Controller in Grid Computing
Distributed heterogeneous architecture is extensively applied to a diversity of large scale research projects conducive to solve complex computational problems. Mentioned distributed systems consist of multiple heterogen...
A Feature Selection Algorithm based on Mutual Information using Local Non-uniformity Correction Estimator
Feature subset selection is an effective approach used to select a compact subset of features from the original set. This approach is used to remove irrelevant and redundant features from datasets. In this paper, a novel...
A Novel Approach for Dimensionality Reduction and Classification of Hyperspectral Images based on Normalized Synergy
During the last decade, hyperspectral images have attracted increasing interest from researchers worldwide. They provide more detailed information about an observed area and allow an accurate target detection and precise...
Enhancement of KaPoW Plugin to Defend Against DDoS Attacks
DDoS attack is one of the hardest attacks to detect and mitigate in the computer world. This paper introduces two quantitative models, which use the client puzzling to detect and thwart application DDoS attacks. We simul...
The Discovery of the Implemented Software Engineering Process Using Process Mining Techniques
Process model guidance is an important feature by which the software process is orchestrated. Without complying with this guidance, the production lifecycle deviates from producing a reliable software with high-quality s...