Surgical strategies for coexisting glaucoma and cataract: an evidence-based update.

OBJECTIVE:

To assess short- and long-term control of intraocular pressure (IOP) with different surgical treatment strategies for coexisting cataract and glaucoma.

DESIGN:

Systematic literature review and analysis.

METHOD:

We performed a search of the published literature to identify all eligible articles pertaining to the surgical management of coexisting cataract and glaucoma in adults. One investigator abstracted the content of each article onto a custom-designed form. A second investigator corroborated the findings. The evidence supporting different approaches was graded by consensus as good, fair, weak, or insufficient.

MAIN OUTCOME MEASURES:

Short-term (24 hours or fewer) and long-term (more than 24 hours) IOP control.

RESULTS:

The evidence was good that long-term IOP is lowered more by combined glaucoma and cataract operations than by cataract operations alone. On average, the IOP was 3 to 4 mmHg lower in the combined groups with fewer medications required. The evidence was weak that extracapsular cataract extraction (ECCE) alone results in short-term increase in IOP and was insufficient to determine the short-term impact of phacoemulsification cataract extraction (PECE) on IOP in glaucoma patients. The evidence was weak that short-term IOP control was better with ECCE or PECE combined with an incisional glaucoma procedure compared with ECCE or PECE alone. The evidence was also weak (but consistent) that long-term IOP is lowered by 2 to 4 mmHg after ECCE or PECE. Finally, there was weak evidence that combined PECE and trabeculectomy produces slightly worse long-term IOP control than trabeculectomy alone, and there was fair evidence that the same is true for ECCE combined with trabeculectomy.

CONCLUSIONS:

There is strong evidence for better long-term control of IOP with combined glaucoma and cataract operations compared with cataract surgery alone. For other issues regarding surgical treatment strategies for cataract and glaucoma, the available evidence is limited or conflicting.

El principio de igualdad de oportunidades en la formaci??n

Resumen basado en el de la publicaci??n

A Newton method for pose refinement of 3D models

Different optimization methods can be employed to optimize a numerical estimate for the match between an instantiated object model and an image. In order to take advantage of gradient-based optimization methods, perspective inversion must be used in this context. We show that convergence can be very fast by extrapolating to maximum goodness-of-fit with Newton's method. This approach is related to methods which either maximize a similar goodness-of-fit measure without use of gradient information, or else minimize distances between projected model lines and image features. Newton's method combines the accuracy of the former approach with the speed of convergence of the latter.

A comparison between feature-based and EM-based contour tracking

Most active-contour methods are based either on maximizing the image contrast under the contour or on minimizing the sum of squared distances between contour and image 'features'. The Marginalized Likelihood Ratio (MLR) contour model uses a contrast-based measure of goodness-of-fit for the contour and thus falls into the first class. The point of departure from previous models consists in marginalizing this contrast measure over unmodelled shape variations. The MLR model naturally leads to the EM Contour algorithm, in which pose optimization is carried out by iterated least-squares, as in feature-based contour methods. The difference with respect to other feature-based algorithms is that the EM Contour algorithm minimizes squared distances from Bayes least-squares (marginalized) estimates of contour locations, rather than from 'strongest features' in the neighborhood of the contour. Within the framework of the MLR model, alternatives to the EM algorithm can also be derived: one of these alternatives is the empirical-information method. Tracking experiments demonstrate the robustness of pose estimates given by the MLR model, and support the theoretical expectation that the EM Contour algorithm is more robust than either feature-based methods or the empirical-information method. (c) 2005 Elsevier B.V. All rights reserved.

Bitmap Movement Detection: HDR for Dynamic Scenes

Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.

Addresses of John Hay.

I. Franklin in France.--II. Omar Khayyám.--III. Sir Walter Scott.--IV. Speeches before the American society in London.--V. A partnership in beneficence.--VI. Speech at the annual dinner of the Royal society.--VII. Speech at the annual dinner of the Literary fund.--VIII. Speech at the opening, by Miss Helen Hay, of the Robert Browning garden.--IX. International copyright.--X. American diplomacy.--XI. A festival of pece.--XII. William McKinley.--XIII. At the universities.--XIV. Commercial club dinner.--XV. New Orleans.--XVI. The Grand army of the republic.--XVII. President Roosevelt.--XVIII. Edmund Clarence Stedman.--XIX. Lincoln's faith.--XX. The press and modern progress.--XXI. Fifty years of the Republican party.--XXII. America's love of peace.--XXIII. Life in the White House in the time of Lincoln.--XXIV. Clarence King.