A Ruggeri1, E Grisan, J Jaroszewski. 1. Department of Information Engineering, University of Padova, 35131 Padova, Italy. alfredo.ruggeri@unipd.it
Abstract
AIMS: The problem of automatic estimation of endothelial cell density from microscopy images in donor corneas was addressed. METHODS: The spatial frequencies contained in digital endothelium images are extracted with a two dimension discrete Fourier transform (DFT) technique. A circular band in the DFT of the images is shown to contain the frequency information related to the cell density. An algorithm for reliably recovering this spatial frequency information and for extracting from it an estimate of endothelial cell density has been developed and implemented in a computer program. An evaluation was performed on a data set containing 100 donor corneas, by comparing automatic values with manual counts performed by three eye bank experts on two images for each cornea. RESULTS: The mean difference of automatic densities v manual ones was 14 cells/mm(2) (0.9%), with a standard deviation of 119 cells/mm(2) (5.1%) and mean absolute difference of 92 cells/mm(2) (3.9%). The ANOVA based overall inter-rater reliability was 0.935. The algorithm was also capable of identifying all non-processable images. Running times were in the order of 1-2 seconds per image. CONCLUSION: A new algorithm was developed for the fully automatic estimation of endothelial cell density. The results of a clinical evaluation on 100 corneas suggest that it is capable of reliably estimating endothelium cell density in donor corneas.
AIMS: The problem of automatic estimation of endothelial cell density from microscopy images in donor corneas was addressed. METHODS: The spatial frequencies contained in digital endothelium images are extracted with a two dimension discrete Fourier transform (DFT) technique. A circular band in the DFT of the images is shown to contain the frequency information related to the cell density. An algorithm for reliably recovering this spatial frequency information and for extracting from it an estimate of endothelial cell density has been developed and implemented in a computer program. An evaluation was performed on a data set containing 100 donor corneas, by comparing automatic values with manual counts performed by three eye bank experts on two images for each cornea. RESULTS: The mean difference of automatic densities v manual ones was 14 cells/mm(2) (0.9%), with a standard deviation of 119 cells/mm(2) (5.1%) and mean absolute difference of 92 cells/mm(2) (3.9%). The ANOVA based overall inter-rater reliability was 0.935. The algorithm was also capable of identifying all non-processable images. Running times were in the order of 1-2 seconds per image. CONCLUSION: A new algorithm was developed for the fully automatic estimation of endothelial cell density. The results of a clinical evaluation on 100 corneas suggest that it is capable of reliably estimating endothelium cell density in donor corneas.
Authors: P Gain; G Thuret; L Kodjikian; Y Gavet; P H Turc; C Theillere; S Acquart; J C Le Petit; J Maugery; L Campos Journal: Br J Ophthalmol Date: 2002-07 Impact factor: 4.638
Authors: Xinwen Yao; Kavya Devarajan; René M Werkmeister; Valentin Aranha Dos Santos; Marcus Ang; Anthony Kuo; Damon W K Wong; Jacqueline Chua; Bingyao Tan; Veluchamy Amutha Barathi; Leopold Schmetterer Journal: Biomed Opt Express Date: 2019-10-11 Impact factor: 3.732
Authors: Oscar E Meruvia-Pastor; Jung Soh; Eric J Schmidt; Julia C Boughner; Mei Xiao; Heather A Jamniczky; Benedikt Hallgrímsson; Christoph W Sensen Journal: Int J Biomed Imaging Date: 2011-05-24