4101 "Imaging the Image" - Enhancing Image Characteristics Of Retinal Images Of Retinopathy Of Prematurity Using An Indigenous Patent Pending Software ("RetiView")

SciVee ◽  
2012 ◽  
Author(s):  
Priyank Solanki ◽  
Anand Vinekar ◽  
Kavitha Avadhani ◽  
Poornima Mohanachandran ◽  
Samit Desai ◽  
...  
Keyword(s):  
Retinopathy Of Prematurity ◽  
Retinal Images ◽  
Image Characteristics ◽  
Image Enhancing

scholarly journals Enhancing Image Characteristics of Retinal Images of Aggressive Posterior Retinopathy of Prematurity Using a Novel Software, (RetiView)

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Chaitra Jayadev ◽  
Anand Vinekar ◽  
Poornima Mohanachandra ◽  
Samit Desai ◽  
Amit Suveer ◽  
...  
Keyword(s):  
Retinopathy Of Prematurity ◽  
Relevant Information ◽  
Retinal Images ◽  
Analysis Software ◽  
Inexpensive Method ◽  
Clinical Exam ◽  
Image Analysis Software ◽  
Image Characteristics ◽  
Indian Origin ◽  
Anterior Extent

Purpose. To report pilot data from a novel image analysis software “RetiView,” to highlight clinically relevant information in RetCam images of infants with aggressive posterior retinopathy of prematurity (APROP).Methods. Twenty-three imaging sessions of consecutive infants of Asian Indian origin with clinically diagnosed APROP underwent three protocols (Grey Enhanced (GE), Color Enhanced (CE), and “Vesselness Measure” (VNM)) of the software. The postprocessed images were compared to baseline data from the archived unprocessed images and clinical exam by the retinopathy of prematurity (ROP) specialist for anterior extent of the vessels, capillary nonperfusion zones (CNP), loops, hemorrhages, and flat neovascularization.Results. There was better visualization of tortuous loops in the GE protocol (56.5%); “bald” zones within the CNP zones (26.1%), hemorrhages (13%), and edge of the disease (34.8%) in the CE images; neovascularization on both GE and CE protocols (13% each); clinically relevant information in cases with poor pupillary dilatation (8.7%); anterior extent of vessels on the VNM protocol (13%) effecting a “reclassification” from zone 1 to zone 2 posterior.Conclusions. RetiView is a noninvasive and inexpensive method of customized image enhancement to detect clinically difficult characteristics in a subset of APROP images with a potential to influence treatment planning.

scholarly journals SEGMENTING THE EYE FUNDUS IMAGES FOR IDENTIFICATION OF BLOOD VESSELS

2012 ◽  
Vol 17 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Gediminas Balkys ◽  
Gintautas Dzemyda
Keyword(s):  
Blood Vessels ◽  
Binary Classification ◽  
Threshold Value ◽  
Retinal Images ◽  
Fundus Images ◽  
Fundus Image ◽  
Image Characteristics ◽  
Selection For ◽  
Binarization Method ◽  
Local Image

Retinal (eye fundus) images are widely used for diagnostic purposes by ophthalmologists. The normal features of eye fundus images include the optic nerve disc, fovea and blood vessels. Algorithms for identifying blood vessels in the eye fundus image generally fall into two classes: extraction of vessel information and segmentation of vessel pixels. Algorithms of the first group start on known vessel point and trace the vasculature structure in the image. Algorithms of the second group perform a binary classification (vessel or non-vessel, i.e. background) in accordance of some threshold. We focus here on the binarization [4] methods that adapt the threshold value on each pixel to the global/local image characteristics. Global binarization methods [5] try to find a single threshold value for the whole image. Local binarization methods [3] compute thresholds individually for each pixel using information from the local neighborhood of the pixel. In this paper, we modify and improve the Sauvola local binarization method [3] by extending its abilities to be applied for eye fundus pictures analysis. This method has been adopted for automatic detection of blood vessels in retinal images. We suggest automatic parameter selection for Sauvola method. Our modification allows determine/extract the blood vessels almost independently of the brightness of the picture.

scholarly journals Retinal vascular development in an immature retina at 33–34 weeks postmenstrual age predicts retinopathy of prematurity

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ji Hye Jang ◽  
Yu Cheol Kim
Keyword(s):  
Preterm Birth ◽  
Preterm Infants ◽  
Gestational Age ◽  
Retinopathy Of Prematurity ◽  
Retinal Images ◽  
Wide Field ◽  
Proliferative Phase ◽  
Postmenstrual Age ◽  
Zone Ii ◽  
Retinal Vascularization

Abstract In preterm birth, the immature retina can develop a potentially blinding disorder of the eye known as retinopathy of prematurity (ROP). The vaso-proliferative phase of ROP begins at an approximate postmenstrual age (PMA) of 32 weeks. There is little or no evidence of an association between ROP development and retinal status in the early vaso-proliferative phase. We aimed to evaluate the retinal vascular findings of infants at 33–34 weeks PMA to determine their risk of ROP. We reviewed 130 serial wide-field retinal images from 65 preterm infants born before the gestational age of 31 weeks. ROP occurred more frequently in infants having a leading vascular edge within posterior Zone II. This was in contrast to normal infants, who are characterized by complete retinal vascularization up to Zone II at 34 weeks PMA. The probability of ROP development in preterm infants with retinal edge hemorrhage was 24.58 times higher than in preterm infants without retinal edge hemorrhage. Eyes with ROP that required treatment showed significantly delayed retinal vascularization accompanied by pre-plus disease. In conclusion, retinal status in the early vaso-proliferation phase might determine the risk of ROP.

Inconsistencies in the Diagnosis of Aggressive Posterior Retinopathy of Prematurity

2017 ◽  
Vol 1 (3) ◽  
pp. 181-186 ◽  
Author(s):  
Samir N. Patel ◽  
Ranjodh Singh ◽  
Karyn E. Jonas ◽  
Susan Ostmo ◽  
Paul Petrakos ◽  
...  
Keyword(s):  
Clinical Diagnosis ◽  
Sensitivity And Specificity ◽  
Retinopathy Of Prematurity ◽  
Retinal Images ◽  
Reference Standard ◽  
Diagnostic Agreement ◽  
Web Based ◽  
Indirect Ophthalmoscopy ◽  
Κ Statistic ◽  
Web Based System

Purpose: To determine the accuracy and reliability of diagnosing aggressive posterior retinopathy of prematurity (AP-ROP). Methods: A total of 1220 eye examinations from 230 infants were prospectively obtained at 8 major ROP centers. An ophthalmologist at each center provided a clinical diagnosis using indirect ophthalmoscopy. Wide-angle retinal images were then obtained, which were independently read by 2 ROP experts using a web-based system for an image-based diagnosis. Sensitivity and specificity of image-based AP-ROP diagnosis by the ROP experts were calculated using the clinical diagnosis as the reference standard. Agreement of AP-ROP diagnosis through image-based diagnosis and clinical diagnosis was calculated using the unweighted κ statistic. Results: One hundred four (9%) of the 1220 examinations had a clinical diagnosis of AP-ROP. Sensitivity and specificity for the presence of AP-ROP were 35% and 96% for expert 1 and 17% and 99% for expert 2. Using the κ statistic, expert image-based versus clinical diagnostic agreement for the diagnosis of AP-ROP was 0.34 (fair) for expert 1 and 0.24 (fair) for expert 2. Agreement for the diagnosis of AP-ROP between the image-based diagnoses of expert 1 and expert 2 was 0.49 (moderate). Conclusion: There are inconsistencies between the clinical diagnosis of AP-ROP (as determined by indirect ophthalmoscopy) and the image-based diagnosis of AP-ROP. This may have important implications for ROP management and the current international ROP classification system.

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