Abstract:
BACKGROUND:The performance of glaucoma diagnostic systems could be conceivably improved by the integration of functional and structural test measurements that provide relevant and complementary information for reaching a diagnosis. The purpose of this study was to investigate the performance of data fusion methods and techniques for simple combination of Standard Automated Perimetry (SAP) and Optical Coherence Tomography (OCT) data for the diagnosis of glaucoma using Artificial Neural Networks (ANNs). METHODS:Humphrey 24-2 SITA standard SAP and StratusOCT tests were prospectively collected from a randomly selected population of 125 healthy persons and 135 patients with glaucomatous optic nerve heads and used as input for the ANNs. We tested commercially available standard parameters as well as novel ones (fused OCT and SAP data) that exploit the spatial relationship between visual field areas and sectors of the OCT peripapillary scan circle. We evaluated the performance of these SAP and OCT derived parameters both separately and in combination. RESULTS:The diagnostic accuracy from a combination of fused SAP and OCT data (95.39%) was higher than that of the best conventional parameters of either instrument, i.e. SAP Glaucoma Hemifield Test (p < 0.001) and OCT Retinal Nerve Fiber Layer Thickness ≥ 1 quadrant (p = 0.031). Fused OCT and combined fused OCT and SAP data provided similar Area under the Receiver Operating Characteristic Curve (AROC) values of 0.978 that were significantly larger (p = 0.047) compared to ANNs using SAP parameters alone (AROC = 0.945). On the other hand, ANNs based on the OCT parameters (AROC = 0.970) did not perform significantly worse than the ANNs based on the fused or combined forms of input data. The use of fused input increased the number of tests that were correctly classified by both SAP and OCT based ANNs. CONCLUSIONS:Compared to the use of SAP parameters, input from the combination of fused OCT and SAP parameters, and from fused OCT data, significantly increased the performance of ANNs. Integrating parameters by including a priori relevant information through data fusion may improve ANN classification accuracy compared to currently available methods.
journal_name
BMC Ophthalmoljournal_title
BMC ophthalmologyauthors
Bizios D,Heijl A,Bengtsson Bdoi
10.1186/1471-2415-11-20subject
Has Abstractpub_date
2011-08-04 00:00:00pages
20issn
1471-2415pii
1471-2415-11-20journal_volume
11pub_type
杂志文章abstract:BACKGROUND:To evaluate results after seven years using prophylactic intracameral cefazolin for the prevention of endophthalmitis in cataract surgery. METHODS:A prospective, observational study of all patients submitted to cataract surgery over the period January 1996 to December 2009. All cases of postoperative endoph...
journal_title:BMC ophthalmology
pub_type: 杂志文章
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journal_title:BMC ophthalmology
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更新日期:2019-12-19 00:00:00
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