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Vessel Width (vessel + width)

Distribution by Scientific Domains
Medical Sciences100%

Selected Abstracts

A comparison of manual and automated methods of measuring conjunctival vessel widths from photographic and digital images

OPHTHALMIC AND PHYSIOLOGICAL OPTICS, Issue 2 2004
Christopher G. Owen
Abstract We investigated the application of a fully automated computer algorithm for identifying vessels of the conjunctiva from their scleral surround, and compared measures of vessel width with established methods. Vessel widths at 101 locations (ranging from 20 to 140 ,m), from 12 patients, were measured from film and digital images, using a variety of methods, and compared. Widths were measured manually, by semi-automated methods using grey level (densitometric) profiles taken from digital images, and by automated techniques set at different operating levels. Good intra-session repeatibility was obtained using the automated method with an operating sigma value of 3 pixels (16 ,m) (mean difference 0.5 ,m, 95% CI ,8.5 to 9.4 ,m) and manual calliper measurements from digitally created photographic slides (mean difference 0.4 ,m, ,9.3 to 10.1 ,m). For comparison with other measures of width, the latter was used as the gold standard. Widths measured from film were slightly larger than those measured directly from digital images, although this effect was small (5 ,m) for most vessels. Overall widths measured using the automated method, with a sigma value of 3 pixels, agreed best with the gold standard (inter-method repeatibility; mean difference 1.4 ,m, ,32.5 to 35.2 ,m) although the automated method overestimated small widths (<40 ,m) and underestimated larger vessel widths (>40 ,m). Automated detection of vessels of the conjunctiva from digital images avoids manual and operator involved measures which are time consuming, and which preclude large patient studies. The resulting data may help in monitoring the vascular response of the conjunctiva to surgical or pharmacological intervention, and in describing vascular changes in response to ocular or systemic disease. The application of this algorithm to the study of retinal vessels is yet to be realised. [source]

Digital image analysis of plus disease in retinopathy of prematurity

ACTA OPHTHALMOLOGICA, Issue 4 2009
Tariq Aslam
Abstract. An accurate assessment of retinopathy of prematurity (ROP) is essential in ensuring correct and timely treatment of this potentially blinding condition. Current modes of assessment are based upon clinical grading by expert examination of retinal changes. However, this may be subjective, unreliable and difficult and there has been significant interest in alternative means of measurement. These have been made possible through technological advancements in image capture and analysis as well as progress in clinical research, highlighting the specific importance of plus disease in ROP. Progress in these two fields has highlighted the potential for digital image analysis of plus disease to be used as an objective, reliable and valid measurement of ROP. The potential for clinical and scientific advancement through this method is argued and demonstrated in this article. Along with the potential benefits, there are significant challenges such as in image capture, segmentation, measurement of vessel width and tortuosity; these are also addressed. After discussing and explaining the challenges involved, the research articles addressing digital image analysis of ROP are critically reviewed. Benefits and limitations of the currently published techniques for digital ROP assessment are discussed with particular reference to the validity and reliability of outcome measures. Finally, the general limitations of current methods of analysis are discussed and more diverse potential areas of development are discussed. [source]

A comparison of manual and automated methods of measuring conjunctival vessel widths from photographic and digital images

OPHTHALMIC AND PHYSIOLOGICAL OPTICS, Issue 2 2004
Christopher G. Owen
Abstract We investigated the application of a fully automated computer algorithm for identifying vessels of the conjunctiva from their scleral surround, and compared measures of vessel width with established methods. Vessel widths at 101 locations (ranging from 20 to 140 ,m), from 12 patients, were measured from film and digital images, using a variety of methods, and compared. Widths were measured manually, by semi-automated methods using grey level (densitometric) profiles taken from digital images, and by automated techniques set at different operating levels. Good intra-session repeatibility was obtained using the automated method with an operating sigma value of 3 pixels (16 ,m) (mean difference 0.5 ,m, 95% CI ,8.5 to 9.4 ,m) and manual calliper measurements from digitally created photographic slides (mean difference 0.4 ,m, ,9.3 to 10.1 ,m). For comparison with other measures of width, the latter was used as the gold standard. Widths measured from film were slightly larger than those measured directly from digital images, although this effect was small (5 ,m) for most vessels. Overall widths measured using the automated method, with a sigma value of 3 pixels, agreed best with the gold standard (inter-method repeatibility; mean difference 1.4 ,m, ,32.5 to 35.2 ,m) although the automated method overestimated small widths (<40 ,m) and underestimated larger vessel widths (>40 ,m). Automated detection of vessels of the conjunctiva from digital images avoids manual and operator involved measures which are time consuming, and which preclude large patient studies. The resulting data may help in monitoring the vascular response of the conjunctiva to surgical or pharmacological intervention, and in describing vascular changes in response to ocular or systemic disease. The application of this algorithm to the study of retinal vessels is yet to be realised. [source]