  Recent studies have demonstrated the diagnostic and prognostic values of
global glomerulosclerosis (GGS) in IgA nephropathy, aging, and end-stage renal
disease. However, the fine-grained quantitative analysis of multiple GGS
subtypes (e.g., obsolescent, solidified, and disappearing glomerulosclerosis)
is typically a resource extensive manual process. Very few automatic methods,
if any, have been developed to bridge this gap for such analytics. In this
paper, we present a holistic pipeline to quantify GGS (with both detection and
classification) from a whole slide image in a fully automatic manner. In
addition, we conduct the fine-grained classification for the sub-types of GGS.
Our study releases the open-source quantitative analytical tool for
fine-grained GGS characterization while tackling the technical challenges in
unbalanced classification and integrating detection and classification.
