Evaluation of asymmetry in right and left eyes of normal individuals using extracted features from optical coherence tomography and fundus images

Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging

“…The current implementation of the proposed method has been tested on the nonperipapillary OCT volume dataset [ 20 ], producing acceptable results in the outermost slices of this volume, where there is enough edge-based information for localizing most of the boundaries. Unlike methods for the 3D segmentation of intraretinal layers based on regional image textures such as, e.g., [ 21 ], the proposed method fails in the central slices of the OCT volume since these edge requirements do not occur. At this point, to overcome this situation, the proposed method could be extended to the 3D case to achieve a robust and more efficient implementation than processing 2D slices of a 3D volume, where the deformable model would be a 3D open active mesh with some a priori knowledge incorporated into the deformable model [ 51 , 52 ] to deal with lack of boundaries of the fiber layers.…”

“…The thickness of the RNFL measured in peripapillary circular OCT scans is an indirect way of assessing the generalized damage that glaucoma produces in the retinal ganglion cells [ 9 ], since the narrowing of the RNFL precedes visual field loss and optic nerve head defects [ 10 , 11 ]. Some of the most popular (and publicly available) databases that can be found are, e.g., Duke SD-OCT [ 12 , 13 ], with 110 OCT B-scans centered at the macula; the dataset described in [ 14 , 15 ], which collects 12 radial OCT B-scans for 61 different subjects; the annotated retinal OCT images (AROI) database [ 16 , 17 ], which is composed of OCT volumes centered on the macula to study the neovascular age-related macular degeneration (nAMD); the OCTID database [ 18 , 19 ], containing retinal fovea-centered 2D OCT images with different pathological conditions; and the dataset contained in [ 20 , 21 ], with volumetric OCTs centered on the macula of left and right eyes of 50 healthy persons. Most of those references are devoted to providing the thickness map of retinal layers, including the RNFL.…”

Synthetic OCT data in challenging conditions: three-dimensional OCT and presence of abnormalities

“…The second dataset is acquired from a Topcon device with a size of 512 × 650 × 128 (dense B-scans) [ 46 ] (available in https://misp.mui.ac.ir/fa/node/1388 ) to prove the effectiveness of the method in different devices and to produce projection images representing the vessel structures. The study was approved by the regional bioethics committee in Isfahan University of Medical Sciences under ethics ID: IR.MUI.MED.REC.1398.697.…”

“…The second dataset is acquired from a Topcon device with a size of 512 × 650 × 128 (dense B-scans) [46] (available in https:// misp. mui.…”

Erratum: Evaluation of asymmetry in right and left eyes of normal individuals using extracted features from optical coherence tomography and fundus images

“…In the article titled “Evaluation of asymmetry in right and left eyes of normal individuals using extracted features from optical coherence tomography and fundus images”, published on pages 12-23, Issue 1, Volume 11 of Journal of Medical Signals and Sensors[ 1 ], the affiliation of Name of the author is written incorrectly as…”