Biomedical subjects

Michael J Cree

Publications and source records attributed to Michael J Cree.

3 recordsLinked to original sources

PubMed2006

Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.

We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et al., 2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver operating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for researchers interested in implementation details, evaluation, or development of methods.

Algorithms↗

PubMed2006

An automated microaneurysm detector as a tool for identification of diabetic retinopathy in rural optometric practice.

BACKGROUND: With the increase in the prevalence of diabetes, rural optometric clinics stand to increase their patient load and assessment of diabetic eye disease. This study aimed to assess whether automated identification of diabetic retinopathy based on the presence of microaneurysms is an effective tool in clinical practice. METHODS: We analysed 758 fundal images of 385 patients with diabetes attending the clinic obtained using a Canon CR5 with an EOS10 digital camera through a dilated pupil. Five optometrists employed in the clinic assessed the diabetic retinopathy using binocular indirect ophthalmoscopy. The sensitivity and specificity of the automated system used to analyse the retinal fundal images was determined by comparison with optometric and ophthalmologic assessment. RESULTS: The optometrists achieved 97 per cent sensitivity at 88 per cent specificity with respect to the ophthalmic classification for detecting retinopathy. CONCLUSION: The automated retinopathy detector achieved 85 per cent sensitivity at 90 per cent specificity at detecting retinopathy. The automated microaneurysm detector has a lower sensitivity compared to the optometrists but meets NHMRC guidelines. It may impact on the efficiency of rural optometric practices by early identification of diabetic retinopathy. Automated assessment can save time and be cost-effective, and provide a history of changes in the retinal fundus and the opportunity for instant patient education using the digital images.

Aneurysm↗

PubMed2003

Automated measurement of microaneurysm turnover.

PURPOSE: An automated system for the measurement of microaneurysm (MA) turnover was developed and compared with manual measurement. The system analyses serial fluorescein angiogram (FA) or red-free (RF) fundus images; fluorescein angiography was used in this study because it is the more sensitive test for MAs. Previous studies have shown that the absolute number of MAs observed does not reflect the dynamic temporal nature of the MA population. In this study, almost half of the MAs present at baseline had regressed after a year and been replaced by new lesions elsewhere. METHODS: Two clinical datasets were used to evaluate the performance of the automated turnover measurement system. The first consisted of 10 patients who had two fluorescein angiograms acquired a year apart. These data were analyzed, both manually and using the automated system, to investigate the inter- and intraobserver variations associated with manual measurement and to assess the performance of the automated system. The second dataset contained FAs from a further 25 patients. This dataset was analyzed only with the automated system to investigate some properties of microaneurysm turnover, in particular the differing detection sensitivities of new, static and regressed microaneurysms. RESULTS: Manual measurements exhibited large inter- and intraobserver variation. The sensitivity and specificity of the automated system were similar to those of the human observers. However, the automated measurements were more consistent-an important condition for accurate turnover quantification. Regressed MAs were more difficult to detect reliably than new MAs, which were themselves more difficult to detect reliably than static MAs. CONCLUSIONS: The automated system was shown to be fast, reliable, and repeatable, making it suitable for processing large numbers of images. Performance was similar to that of trained manual observers.

Adult↗