@article {269, title = {Alignment of confocal scanning laser ophthalmoscopy photoreceptor images at different polarizations using complex phase relationships}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {56}, year = {2010}, abstract = {

A polarimetric technique for enhancing fundus images was recently introduced , where confocal scanning laser ophthalmoscopy (CSLO) images are acquired under differing incoming polarization states, and spatially resolved Mueller images are constructed based on the images. An important stage in this technique is the alignment of CSLO images acquired under differing polarization states. This has proven to be particularly difficult when dealing with photoreceptor images, which are characterized by poor SNRs and intensity inhomogeneities due to polarization properties. In this paper, an automated approach to aligning CSLO photoreceptor images acquired under differing polarization states is presented. A novel energy functional based on complex phase relationships is introduced that is invariant to polarization and scale, as well as robust to noise and highly sensitive to photoreceptor structural characteristics. A sequential quadratic programming approach is employed to determine the optimal alignment between the photoreceptor images by minimizing the proposed energy functional. The method has been tested on CSLO fish photoreceptor images acquired under differing polarization states and evaluated based on alignment accuracy. The results demonstrate that the proposed method outperforms existing techniques used for aligning CSLO images, with lower mean alignment error for all test cases.

}, keywords = {Algorithms, Animals, bio-optics, biomedical optical imaging, complex phase relationship, Computer-Assisted, Confocal, confocal scanning laser ophthalmoscopy, enhancing fundus image, eye, Fishes, Fundus Oculi, image enhancement, image processing, incoming polarization states, laser applications in medicine, light polarisation, medical image processing, Microscopy, Ophthalmoscopy, Photoreceptor Cells, photoreceptor image, polarimetry, Polarization, quadratic programming, sequential quadratic programming, spatially resolved Mueller image construction, Thermodynamics, Vertebrate}, issn = {0018-9294}, doi = {http://dx.doi.org/10.1109/TBME.2009.2017510}, author = {A Wong} } @inproceedings {289, title = {A novel algorithm for extraction of the layers of the cornea}, booktitle = {6th Canadian Conference on Computer and Robot Vision}, year = {2009}, month = {05/2009}, address = {Kelowna, British Columbia, Canada}, abstract = {

Accurate corneal layer boundary extraction from optical coherence tomograms can provide precise layer thickness measurements required in the analysis of corneal disease. This paper establishes a novel approach to precisely obtain the five primary corneal layer boundaries. The proposed method determines correspondence relationships between the layer boundaries to facilitate robust boundary extraction in the presence of noise and artifacts. The first phase of the method applies morphological operators to enhance the prominent structural features of the cornea. The second phase uses a semi-automated segmentation algorithm to extract the upper and lower boundaries of the cornea; these boundaries are used to register the corneal image. The final phase extracts all five boundaries using a global optimization method exploiting the medial correspondence relationship between each layers. The proposed method is tested and verified using a representative set of optical coherence tomography images and compared against several state of the art methods. The proposed method is demonstrated to be more robust to noise, to provide more accurate segmentation results, and to require fewer user interactions than the other published methods.

}, keywords = {corneal disease, corneal image register, corneal layer boundary extraction, diseases, eye, Feature Extraction, global optimization method, image registration, image segmentation, layer thickness measurements, medical image processing, optical coherence tomography, optical tomography, optimisation, semiautomated segmentation algorithm, thickness measurement}, doi = {http://dx.doi.org/10.1109/CRV.2009.22}, author = {J A. Eichel and A Mishra and D A. Clausi and P Fieguth} } @inproceedings {337, title = {Perceptually-adaptive color enhancement of still images for dichromacy deficiencies}, booktitle = {21st Canadian Conference on Electrical and Computer Engineering}, year = {2008}, abstract = {

Dichromacy is a medical condition in which a person is unable to distinguish all colors of the spectrum accurately due to the absence of one cone type within the retina of the eye. No known cure exists for dichromacy so techniques have been created to help improve color perception among affected individuals. This paper investigates a novel perceptually-adaptive technique for enhancing details within still images for persons suffering from dichromacy. A non-linear hue remapping is adaptively applied to the still images to improve color differentiation while preserving the aesthetics of the images. Simulations show that the enhanced images preserve visual detail and maintain the aesthetics of the original image.

}, keywords = {color perception, colour vision, dichromacy, eye, image colour analysis, image enhancement, nonlinear hue remapping, perceptually-adaptive technique, retina, vision defects, visual perception}, doi = {http://dx.doi.org/10.1109/CCECE.2008.4564901}, author = {A Wong and W Bishop} } @inproceedings {499, title = {Analysis of corneal images for assessing contact lens trauma}, booktitle = {International Conference on Image Processing}, year = {2000}, address = {Vancouver}, abstract = {

Contact lens wearers are often affected by a condition known as conjuctival hyperaemia. This condition is characterised by dilated blood vessels visible in the sclera (the white portion of the eye). Optometrists need to be able to detect changes in the level of redness and to repeatably assess the absolute levels of redness found in a patient\&$\#$39;s eye in order to prescribe and evaluate treatment. The goal of this paper is to develop an automated method for grading the level of redness in human eyes. The selected features examine the average redness and length of arterial edges. The computed features are correlated with expert data collected to train the redness estimator

}, keywords = {arterial edges, blood vessels, conjuctival hyperaemia, contact lens trauma, corneal images, dilated blood vessels, edge detection, eye, Feature Extraction, human eyes, image colour analysis, medical image processing, patient, redness, redness estimator, sclera}, doi = {http://dx.doi.org/10.1109/ICIP.2000.900923}, author = {J Cullen and P Fieguth and S Pounder and K Whitear} }