Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 7
Abstract
Segmentation on the trabecular of dental periapical X-Ray images is very important for osteoporosis screening. Existing methods do not perform well in segmenting the trabecular of dental periapical in X-Ray images due to the presence of large amount of spurious edges. This paper presents a combination of tophat-bothat filtering, histogram equalization contrasting and local adaptive thresholding approach for automatic segmentation of dental periapical in X-Ray images. The qualitative evaluation is done by a dentist and shows that the proposed segmentation algorithm performed well the porous of trabecular features of dental periapical. The quantitative evaluation used fuzzy classification based on neural network to classify these features. It were found accuracy rate to be 99,96% for training set and around 65% for testing set for a dataset of 60 subjects.
Authors and Affiliations
Enny Sela, Sri Hartati, Agus Harjoko, Retantyo Wardoyo, Munakhir MS
Linking Context to Data Warehouse Design
Data warehouses are now widely used for analysis and decision support purposes. The availability of software solutions, which are more and more user-friendly and easy to manipulate has made it possible to extend their us...
Impedance Matching of a Microstrip Antenna
Microstrip patch antennas play a very significant role in communication systems. In recent years, the study to improve their performances has made great progression, and different methods have been proposed to optimize t...
E-learning Document Search Method with Supplemental Keywords Derived from Keywords in Meta-Tag and Descriptions which are Included in the Header of the First Search Result
Optimization method for e-learning document search with keywords which are derived from the keywords and descriptions in the meta-tag of web search results together with thesaurus engine is proposed. 15 to 20% of i...
Developing Disease Classification System based on Keyword Extraction and Supervised Learning
The Evidence-Based Medicine (EBM) is emerged as the helpful practice for medical practitioners to make decisions with available shreds of evidence along with their professional ex-pertise. In EBM, the medical practitione...
Optimum Access Analysis of Collaborative Spectrum Sensing in Cognitive Radio Network using MRC
The performance of cognitive radio network mainly depends on the finest sensing of the presence or absence of Primary User (PU). The throughput of a Secondary User (SU) can be reduced because of the false detection of PU...