Unsupervised labeling of glomerular boundaries using Gabor filters and statistical testing in renal histology.
The glomerulus is the blood filtering unit of the kidney. Each human kidney contains [Formula: see text] glomeruli. Several renal conditions originate from structural damage to glomerular microcompartments, such as proteinuria, the excessive loss of blood proteins into urine. The gold standard for evaluating structural damage in renal pathology is histopathological and immunofluorescence examination of needle biopsies under a light microscope. This method is limited by qualitative or semiquantitative manual scoring approaches to the evaluation of glomerular structural features. Computational quantification of equivalent features promises to improve the precision of glomerular structural analysis. One large obstacle to the computational quantification of renal tissue is the identification of complex glomerular boundaries automatically. To mitigate this issue, we developed a computational pipeline capable of extracting and exactly defining glomerular boundaries. Our method, composed of Gabor filtering, Gaussian blurring, statistical [Formula: see text]-testing, and distance transform, is able to accurately identify glomerular boundaries with mean sensitivity/specificity of [Formula: see text] and accuracy of 0.92, on [Formula: see text] glomeruli images stained with standard renal histological stains. Our method will simplify computational partitioning of glomerular microcompartments hidden within dense textural boundaries. Automatic quantification of glomeruli will streamline structural analysis in clinic and can pioneer real-time diagnoses and interventions for renal care.
University at Buffalo-The State University of New York , Departments of Pathology and Anatomical Sciences, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States.
Brandon
B
Ginley
University at Buffalo-The State University of New York, Departments of Pathology and Anatomical Sciences, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States; University at Buffalo-The State University of New York, Departments of Biomedical Informatics, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States.
John E
JE
Tomaszewski
University at Buffalo-The State University of New York , Departments of Medicine-Nephrology, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States.
Rabi
R
Yacoub
Washington University School of Medicine in Saint Louis , Department of Medicine-Renal Division, Campus Box 8126, St. Louis, Missouri 63110, United States.
Feng
F
Chen
University at Buffalo-The State University of New York, Departments of Pathology and Anatomical Sciences, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States; University at Buffalo-The State University of New York, Departments of Biomedical Engineering, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States; University at Buffalo-The State University of New York, Departments of Biostatistics, 207 Farber Hall, 3435 Main Street Buffalo, New York 14214, United States.
Pinaki
P
Sarder
F-test; Gabor filtering; digital pathology; glomerulus; texture analysis