23,99 €
inkl. MwSt.
Versandfertig in 6-10 Tagen
12 °P sammeln
Andere Kunden interessierten sich auch für
![On the Estimation of Survival Time and Identification]( "On the Estimation of Survival Time and Identification")
On the Estimation of Survival Time and Identification40,99 €![Identification and motivation of high potentials to keep their intellectual property in the company]( "Identification and motivation of high potentials to keep their intellectual property in the company")
Identification and motivation of high potentials to keep their intellectual property in the company47,95 €![The Effect of Entrepreneurial Orientation on the Relationship between Opportunity Identification and Enterprise Growth of SMEs in Zambia]( "The Effect of Entrepreneurial Orientation on the Relationship between Opportunity Identification and Enterprise Growth of SMEs in Zambia")
The Effect of Entrepreneurial Orientation on the Relationship between Opportunity Identification and Enterprise Growth of SMEs in Zambia24,99 €![Intelligent Breast Cancer Identification System]( "Intelligent Breast Cancer Identification System")
Intelligent Breast Cancer Identification System32,99 €![Biological Studies on some Bivalves]( "Biological Studies on some Bivalves")
Biological Studies on some Bivalves60,99 €![Antibiotic Susceptibility Patterns of Pathogenic Bacteria]( "Antibiotic Susceptibility Patterns of Pathogenic Bacteria")
Antibiotic Susceptibility Patterns of Pathogenic Bacteria26,99 €![Latent Fingerprint Identification Using Deep Learning Method]( "Latent Fingerprint Identification Using Deep Learning Method")
Latent Fingerprint Identification Using Deep Learning Method26,99 €
RA is a dangerous and chronic disease that should be analyzed and detected in its early stages. Thus, the aim of this thesis is to develop a new approach for the identification of rheumatoid arthritis through knee image processing techniques and neural network classifier. Thus, any supplied knee image must be classified either normal or abnormal. The proposed system uses knees images obtained from a created database comprised of 300 images for training and 300 images for testing phase. The used image processing techniques facilitate the diagnosis of that disease by analyzing and pointing out the rheumatoid arthritis signs and symptoms through extracting the useful and needed features or patterns such as the distance between the femoral and tibial bones, joint damage, bone widening and stiffening. Moreover,the developed system helps the doctors to accurately classify the RA knee X-ray images since it is designed to stimulate the human visual inspection that is based on visualizingsome related features and signs of RA.