AIM: The evaluation of inner retinal layer thickness can serve as a direct biomarker for monitoring the course of @entity6220 such as @entity15 ( @entity15 ). Using optical coherence tomography (OCT), thinning of the retinal nerve fibre layer and changes in deeper retinal layers have been observed in @entity1 with @entity15 . Here, we first compare a novel method for automated segmentation of OCT images with manual segmentation using two cohorts of @entity1 with @entity15 . Using this method, we also aimed to reproduce previous findings showing @entity2000 following @entity7995 ( @entity7995 ) in @entity15 . METHODS: Based on a 5*5 expansion of the Prewitt operator to efficiently calculate the gradient of image intensity, we introduce an automated algorithm for the segmentation of intraretinal layers. We evaluated this algorithm by comparison to manually segmented two-dimensional OCT images at the macular level for 125 @entity1 from two separate cohorts of @entity1 with @entity15 . Of these @entity1 , 52 had suffered from unilateral @entity7995 + within 6   months prior to measurement. RESULTS: When comparing @entity7995 + eyes with @entity735 , both manual and automated segmentation demonstrated a significant inter-eye thinning in the ganglion cell layer in @entity7995 + eyes. We also observed an increased thickness of the inner nuclear (INL) and the outer segment-retinal pigment epithelium (OS-RPE) layers of @entity7995 + eyes in both cohorts. These findings corroborate previous data, thus demonstrating the validity of our approach. CONCLUSIONS: The algorithm presented here was found to be a valid tool for replacing cumbersome manual segmentation methods in the quantification of inner retinal layers in OCT. The observed increases in thickness of INL and OS-RPE may be attributed to primary @entity989 , repair and/or plasticity mechanisms following the immune attack.

A novel automated segmentation method for retinal layers in OCT images proves @entity2000 after XXXX .

@entity1 :: ('9606', 'Species') :: ['patients'] @entity2000 :: ('MESH:D012162', 'Disease') :: ['retinal degeneration'] @entity6220 :: ('MESH:D020279', 'Disease') :: ['inflammatory diseases of the central nervous system'] @entity7995 :: ('MESH:D009902', 'Disease') :: ['optic neuritis', 'ON'] @entity735 :: ('MESH:D005124', 'Disease') :: ['ON- eyes'] @entity989 :: ('MESH:D012164', 'Disease') :: ['retinal inflammation'] @entity15 :: ('MESH:D009103', 'Disease') :: ['MS', 'multiple sclerosis']
@entity7995 :: (MESH:D009902,Disease) :: ['optic neuritis']
