Yue Di1, Ying Huang1, Ya-Jing Yang2, Xing-Tao Zhou3, Wen-Ting Luo1, Hai-Yun Ye1, Zhong-Bao Qiao1, Na Lu4, Tong Qiao1. 1. Department of Ophthalmology, Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai 200062, China. 2. Department of Ophthalmology, East Hospital Affiliated to Tongji University, Shanghai 200120, China. 3. Department of Ophthalmology, Eye & ENT Hospital Fudan University, Shanghai 200031, China. 4. Department of Radiology, Huashan Hospital North, Fudan University, Shanghai 200040, China.
Abstract
AIM: To identify the guinea pig eyeball with edge detection and curve fitting and devise a noncontact technology of measuring ocular morphological parameters of small experimental animal. METHODS: Thirty-nine eyeballs of guinea pig eyeballs were photographed to obtain the anterior and posterior surface; transverse and sagittal planes after the eyeballs were eviscerated. Next, the eyeball photos were input into digital image analysis software; the corresponding photo pixels-actual length ratio was acquired by a proportional scale. The contour lines of the eyeballs were identified by edge detection technology; conic curve fitting was applied to fit the contour line of the eyeball. The maximum and minimum diameters, the horizontal and vertical diameters, eccentricity, tilt angle, cross-sectional area, equatorial circumference, retrobulbar equatorial maximum length, corneal radius of curvature (CRC) in central region, and the whole cornea were calculated according to the geometric principles. The corneal data of in vitro study were compared with the in vivo results. RESULTS: The contour line of the selected guinea pig eye was identified correctly by edge detection. There were no significant differences between anterior and posterior surfaces of one eyeball in the maximum diameters, eccentricity, cross-sectional area, equatorial circumference, and tilt angle (P > 0.01). There were significant differences of eccentricity and CRC between central region and the whole cornea (P < 0.01). There were no significant differences between keratometer in vivo and cornea in vitro. CONCLUSION: It was feasible to measure an experimental animal eye in a noncontact way. Edge detection and curve fitting technology could accurately evaluate the ocular morphological parameters.
AIM: To identify the guinea pig eyeball with edge detection and curve fitting and devise a noncontact technology of measuring ocular morphological parameters of small experimental animal. METHODS: Thirty-nine eyeballs of guinea pig eyeballs were photographed to obtain the anterior and posterior surface; transverse and sagittal planes after the eyeballs were eviscerated. Next, the eyeball photos were input into digital image analysis software; the corresponding photo pixels-actual length ratio was acquired by a proportional scale. The contour lines of the eyeballs were identified by edge detection technology; conic curve fitting was applied to fit the contour line of the eyeball. The maximum and minimum diameters, the horizontal and vertical diameters, eccentricity, tilt angle, cross-sectional area, equatorial circumference, retrobulbar equatorial maximum length, corneal radius of curvature (CRC) in central region, and the whole cornea were calculated according to the geometric principles. The corneal data of in vitro study were compared with the in vivo results. RESULTS: The contour line of the selected guinea pig eye was identified correctly by edge detection. There were no significant differences between anterior and posterior surfaces of one eyeball in the maximum diameters, eccentricity, cross-sectional area, equatorial circumference, and tilt angle (P > 0.01). There were significant differences of eccentricity and CRC between central region and the whole cornea (P < 0.01). There were no significant differences between keratometer in vivo and cornea in vitro. CONCLUSION: It was feasible to measure an experimental animal eye in a noncontact way. Edge detection and curve fitting technology could accurately evaluate the ocular morphological parameters.
Authors: Choon-Hwai Yap; Karl Thiele; Qifeng Wei; Arvind Santhanakrishnan; Reza Khiabani; Michael Cardinale; Ivan S Salgo; Ajit P Yoganathan Journal: IEEE Trans Ultrason Ferroelectr Freq Control Date: 2013-07 Impact factor: 2.725