Author/Authors :
ghanian, zahra university of wisconsin milwaukee - department of electrical engineering and computer science, biophotonics laboratory, usa , staniszewski, kevin university of wisconsin milwaukee - department of electrical engineering and computer science, biophotonics laboratory, USA , jamali, nasim university of wisconsin - school of medicine and public health - department of ophthalmology and visual sciences, USA , sepehr, reyhaneh university of wisconsin milwaukee - department of electrical engineering and computer science, biophotonics laboratory, usa , wang, shoujian university of wisconsin - school of medicine and public health - department of ophthalmology and visual sciences, usa , sorenson, christine m. university of wisconsin - mcpherson eye research institute, school of medicine and public health - department of pediatircs, usa , sheibani, nader university of wisconsin - mcpherson eye research institute, school of medicine and public health - departments of ophthalmology and visual sciences and biomedical engineering, USA , ranji, mahsa university of wisconsin milwaukee - mcpherson eye research institute, school of medicine and public health - department of electrical engineering and computer science, biophotonics laboratory, USA
Abstract :
A multi‑parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl‑2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e‑05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e‑04; an indicator of PC loss), higher fractal dimension (P = 8.2202e‑05), smaller vessel coverage (P = 1.4214e‑05), and greater number of acellular capillaries (P = 7.0414e‑04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high‑throughput and reproducible manner.
Keywords :
Classification , fluorescence microscopy , fractals , image cytometry , retinopathy , segmentation
