RESUMEN
BACKGROUND AND OBJECTIVE: To report a method to track the pupil in three axes simultaneously prior to imaging the fundus. PATIENTS AND METHODS: The system is based on parallax optical alignment to detect the center of the pupil. The system consists of two cameras acquiring pupil images from two distinct directions and an operator-supervised algorithm to derive the coordinates of the pupil center and output of commands to drive a three-axes computer-controlled stage. The system was tested in a cohort of 45 individuals 61 ± 15 years of age, 26 with and 19 without glaucoma. The tracking was performed without pharmacologic pupil dilation. RESULTS: The variability of the pupil center determination (assessed by the standard deviation) was ± 0.19 and ± 0.33 mm for the vertical and horizontal directions, respectively. The processing time of the algorithm was 0.75 msec. The tracking converged to within a preset tolerance of ± 0.5 mm in 45 of the 45 eyes. CONCLUSION: Image acquisition and processing of pupil images can be used to align fundus imaging systems rapidly, accurately, and with minimal operator intervention.
Asunto(s)
Fondo de Ojo , Procesamiento de Imagen Asistido por Computador/métodos , Pupila , Anciano , Algoritmos , Automatización , Estudios de Cohortes , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador/normas , Masculino , Persona de Mediana Edad , Proyectos Piloto , Factores de TiempoRESUMEN
Optic disc photography is used in the management and study of glaucoma. Quality assessment is needed at the time of acquisition and during review. A computerized algorithm for objective quality assessment was developed to mimic the procedure used by human observers. It was tested on film-based images obtained with mydriasis (40 normal and 46 glaucomatous eyes) and non-mydriatic digital images (30 normal and 38 glaucomatous eyes). The image sharpness was graded by six masked readers into four categories. The area under the receiver operating characteristic curve for identifying unreadable images was 1.0 for the digital and film-based images and 0.91 and 1.0 for differentiating between unreadable and mediocre images for digital and film-based images, respectively. This pilot study demonstrates that the algorithm can identify all unreadable images. Further studies are necessary to test whether it can be applied to images obtained in other locations on the fundus and with additional cameras.
Asunto(s)
Algoritmos , Glaucoma/diagnóstico , Procesamiento de Imagen Asistido por Computador/normas , Disco Óptico/patología , Fotograbar/instrumentación , Diseño de Equipo , Humanos , Procesamiento de Imagen Asistido por Computador/instrumentación , Fotograbar/normas , Control de Calidad , Reproducibilidad de los ResultadosRESUMEN
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.