Abstract:
According to WHO, non-communicable diseases (NCDs) were responsible for 68% of all deaths globally in 2012, up from 60% in 2000. The four main NCDs are cardiovascular diseases, cancers, diabetes and chronic lung diseases. In most of the diseases, morphological and / or functional characteristics of cell facilitate researchers and clinicians to determine the cell state (i.e. diseased or healthy, disease state, etc). In recent years, high-resolution imaging approaches (ex. confocal microscopy) are used to study and understand the morphological characteristics of the cell. In addition, there are few computational tools developed to process these high-resolution imaging images to identify the cell state. Polyfiberquant is one of the unique software tool for cell state prediction. But the sensitivity and specificity of the tool is primarily dependent on the parameters used in the prediction. Therefore, the primary goal of this study is to find the best parameters that can be used in Polyfiberquant tool that result in reliable cell state prediction using confocal microscopy images. Secondarily, the study will also determine the limitations of this tool.
