Literature DB >> 17956367

Image quality characteristics of a novel colour scanning digital ophthalmoscope (SDO) compared with fundus photography.

Rupert W Strauss1, Tina R Krieglstein, Siegfried G Priglinger, Werner Reis, Michael W Ulbig, Anselm Kampik, Aljoscha S Neubauer.   

Abstract

PURPOSE: To establish a set of quality parameters for grading image quality and apply those to evaluate the fundus image quality obtained by a new scanning digital ophthalmoscope (SDO) compared with standard slide photography.
METHODS: On visual analogue scales a total of eight image characteristics were defined: overall quality, contrast, colour brilliance, focus (sharpness), resolution and details, noise, artefacts and validity of clinical assessment. Grading was repeated after 4 months to assess repeatability. Fundus images of 23 patients imaged digitally by SDO and by Zeiss 450FF fundus camera using Kodak film were graded side-by-side by three graders. Lens opacity was quantified with the Interzeag Lens Opacity Meter 701.
RESULTS: For all of the eight scales of image quality, good repeatability within the graders (mean Kendall's W 0.69) was obtained after 4 months. Inter-grader agreement ranged between 0.31 and 0.66. Despite the SDO's limited nominal image resolution of 720 x 576 pixels, the Zeiss FF 450 camera performed better in only two of the subscales - noise (p = 0.001) and artefacts (p = 0.01). Lens opacities significantly influenced only the two subscales 'resolution' and 'details', which deteriorated with increasing media opacities for both imaging systems.
CONCLUSIONS: Distinct scales to grade image characteristics of different origin were developed and validated. Overall SDO digital imaging was found to provide fundus pictures of a similarly high level of quality as expert photography on slides.

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Year:  2007        PMID: 17956367     DOI: 10.1111/j.1475-1313.2007.00512.x

Source DB:  PubMed          Journal:  Ophthalmic Physiol Opt        ISSN: 0275-5408            Impact factor:   3.117


  4 in total

1.  Megahertz ultra-wide-field swept-source retina optical coherence tomography compared to current existing imaging devices.

Authors:  Lukas Reznicek; Thomas Klein; Wolfgang Wieser; Marcus Kernt; Armin Wolf; Christos Haritoglou; Anselm Kampik; Robert Huber; Aljoscha S Neubauer
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2014-05-01       Impact factor: 3.117

2.  Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

Authors:  Aaron S Coyner; Ryan Swan; James M Brown; Jayashree Kalpathy-Cramer; Sang Jin Kim; J Peter Campbell; Karyn E Jonas; Susan Ostmo; R V Paul Chan; Michael F Chiang
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

3.  Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

Authors:  Aaron S Coyner; Ryan Swan; J Peter Campbell; Susan Ostmo; James M Brown; Jayashree Kalpathy-Cramer; Sang Jin Kim; Karyn E Jonas; R V Paul Chan; Michael F Chiang
Journal:  Ophthalmol Retina       Date:  2019-01-31

Review 4.  Smartphone Sensors for Health Monitoring and Diagnosis.

Authors:  Sumit Majumder; M Jamal Deen
Journal:  Sensors (Basel)       Date:  2019-05-09       Impact factor: 3.576

  4 in total

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