No abstract

No abstract

No abstract

Hematoxylin and eosin (H and E) is one of the common histological staining techniques that provides information on the tissue cytoarchitecture. Adipose (fat) cells accumulation in pancreas has been shown to impact beta cell survival and its endocrine function. The current automated tools available for fat analysis are suited for white adipose tissue which is homogeneous and easier to segment unlike heterogeneous tissues such as pancreas where fat cells continue to play critical physiopathological functions. In the current study, we present an automated fat analysis tool, Fatquant, where mathematical formula to calculate diagonal of a square drawn inside circle is utilized for identification and analysis of fat cells in heterogeneous H and E tissue sections. Using histological images of pancreas from a publicly available database, we show an area accuracy overlap of 89-93% between manual versus automated algorithm based fat cell detection.