The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the GaussMarkov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, vide...

The current mode of clinical aided diagnosis Ocular Myasthenia Gravis (OMG) is time-consuming and laborious, it lacks quantitative standards. An diagnostic system for OMG proposed to solve this problem. values calculated by the include three indicators: eyelid distance, sclera palpebra superior fatigability test time. For first two indicators, semantic segmentation method was used extract patho...

Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered emotions (cataplexy). A recent approach for the diagnosis disease based on completely manual analysis video recordings patients undergoing emotional stimulation made on-site medical specialists, looking specific facial behavior motor phenomena. We present h...

The greatest cause of death for both men and women globally is lung cancer. This mostly because it manifests no symptoms at first only identified a late stage, when the patient's condition has already gotten worse. Typically, skilled expert will thoroughly examine CT scans to make diagnosis Finding interpreting abnormalities on scan can be quite challenging, even highly medical professionals. I...

BACKGROUND Differentiating pancreatic cancer (PC) from normal tissue by computer-aided diagnosis of EUS images were quite useful. The current study was designed to investigate the feasibility of using computer-aided diagnostic (CAD) techniques to extract EUS image parameters for the differential diagnosis of PC and chronic pancreatitis (CP). METHODOLOGY/PRINCIPAL FINDINGS This study recruited...