TY - JOUR
T1 - An Image based auto-focusing algorithm fordigital fundus photography
AU - Moscaritolo, Michele
AU - Jampel, Henry
AU - Knezevich, Frederick
AU - Zeimer, Ran
N1 - Funding Information:
Manuscript received February 24, 2009; revised March 20, 2009. First published April 10, 2009; current version published October 28, 2009. This work was supported in part by P30 EY01765 core grant from the National Eye Institute Bethesda, MD, ROI EYO 16133 (R. Zeimer) ROI EYO 17053 (H. Jampel), in part by the Wilmer Telemedicine Fund, and in part by an unrestricted grant from Eyetel-Imaging. Under an agreement between Eyetel-Imaging and the Johns Hopkins University, R. Zeimer is entitled to a share of sales royalty received by the University. The terms of this agreement have been reviewed and approved by the University in accordance with its conflict of interest policies. Asterisk indicates corresponding author. *M. Moscaritolo is with the Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287 USA, and also with Department of Physics, University of Siena, 53100 Siena, Italy (e-mail: michele@jhmi.edu).
PY - 2009/11
Y1 - 2009/11
N2 - In fundus photography, the task of fine focusing the image is demanding and lack of focus is quite often the cause of suboptimal photographs. The introduction of digital cameras has provided an opportunity to automate the task of focusing. We have developed a software algorithm capable of identifying best focus. The auto-focus (AF) method is based on an algorithm we developed to assess the sharpness of an image. The AF algorithm was tested in the prototype of a semi-automated nonmydriatic fundus camera designed to screen in the primary care environment for major eye diseases. A series of images was acquired in volunteers while focusing the camera on the fundus. The image with the best focus was determined by the AF algorithm and compared to the assessment of two masked readers. A set of fundus images was obtained in 26 eyes of 20 normal subjects and 42 eyes of 28 glaucoma patients. The 95% limits of agreement between the readers and the AF algorithm were ${-}2.56$ to 2.93 and ${-}3.7$ to 3.84 diopter and the bias was 0.09 and 0.71 diopter, for the two readers respectively. On average, the readers agreed with the AF algorithm on the best correction within less than $3/4$ diopter. The intraobserver repeatability was 0.94 and 1.87 diopter, for the two readers respectively, indicating that the limit of agreement with the AF algorithm was determined predominantly by the repeatability of each reader. An auto-focus algorithm for digital fundus photography can identify the best focus reliably and objectively. It may improve the quality of fundus images by easing the task of the photographer.
AB - In fundus photography, the task of fine focusing the image is demanding and lack of focus is quite often the cause of suboptimal photographs. The introduction of digital cameras has provided an opportunity to automate the task of focusing. We have developed a software algorithm capable of identifying best focus. The auto-focus (AF) method is based on an algorithm we developed to assess the sharpness of an image. The AF algorithm was tested in the prototype of a semi-automated nonmydriatic fundus camera designed to screen in the primary care environment for major eye diseases. A series of images was acquired in volunteers while focusing the camera on the fundus. The image with the best focus was determined by the AF algorithm and compared to the assessment of two masked readers. A set of fundus images was obtained in 26 eyes of 20 normal subjects and 42 eyes of 28 glaucoma patients. The 95% limits of agreement between the readers and the AF algorithm were ${-}2.56$ to 2.93 and ${-}3.7$ to 3.84 diopter and the bias was 0.09 and 0.71 diopter, for the two readers respectively. On average, the readers agreed with the AF algorithm on the best correction within less than $3/4$ diopter. The intraobserver repeatability was 0.94 and 1.87 diopter, for the two readers respectively, indicating that the limit of agreement with the AF algorithm was determined predominantly by the repeatability of each reader. An auto-focus algorithm for digital fundus photography can identify the best focus reliably and objectively. It may improve the quality of fundus images by easing the task of the photographer.
KW - Digital fundus photography
KW - Focus
KW - Image processing
KW - Sharpness
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U2 - 10.1109/TMI.2009.2019755
DO - 10.1109/TMI.2009.2019755
M3 - Article
C2 - 19366641
AN - SCOPUS:70350770985
SN - 0278-0062
VL - 28
SP - 1703
EP - 1707
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 11
M1 - 4813255
ER -