Ghulam Ali Mallah¹, Jamil Ahmed¹, Muhammad Irshad Nazeer^2,*, Mazhar Ali Dootio³, Hidayatullah Shaikh¹, Aadil Jameel¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5343-5353, 2022, DOI:10.32604/cmc.2022.023581

Abstract Detection of abnormalities in human eye is one of the well-established research areas of Machine Learning. Deep Learning techniques are widely used for the diagnosis of Retinal Diseases (RD). Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels (PBV). Retinopathy Images (RI) contains sufficient information to classify structural changes incurred upon PBV but Macular Features (MF) and Fovea Features (FF) are very difficult to detect because features of MF and FF could be found with Similar Color Movements (SCM) with minor variations. This paper presents novel method for the… More >

Sungjin Lee¹, Min Hong², Hongly Va¹, Ji-Yun Park^3,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3669-3679, 2021, DOI:10.32604/cmc.2021.015706

Abstract Subjective visual vertical (SVV) and subjective visual horizontal (SVH) tests can be used to evaluate the perception of verticality and horizontality, respectively, and can aid the diagnosis of otolith dysfunction in clinical practice. In this study, SVV and SVH screen version tests are implemented using virtual reality (VR) equipment; the proposed test method promotes a more immersive feeling for the subject while using a simple equipment configuration and possessing excellent mobility. To verify the performance of the proposed VR-based SVV and SVH tests, a reliable comparison was made between the traditional screen-based SVV and SVH tests and the proposed method,… More >