The purpose of this project is to study the risk of cataract development in patients who had undergone pars plana vitrectomy, scleral buckle, or both. A retrospective study was performed of phakic patients who underwent pars plana vitrectomy, scleral buckle, or both at Yale University Eye Center from 1998 to 2005. Mild postoperative cataract, defined as a change in severity of 1+, developed in 32 of 53 (60%) eyes following vitrectomy, 2 of 19 (11%) post scleral buckle, and 14 of 16 (88%) after both. Moderate postoperative cataract, defined as a change in severity of 2+, developed in 14 of 53 (26%) eyes post vitrectomy, 1 of 19 (5%) post scleral buckle, and 11 of 16 (69%) after both procedures. In eyes that underwent vitrectomy, a lens change of at least 2+ occurred in 8% at 3 months, 15% at 6 months, 21% at 12 months, and 26% at 36 months. In eyes status post scleral buckle surgery, one eye (5%) experienced a 2+ change at 36 months. In eyes that underwent both vitrectomy and scleral buckle, a lens change of at least 2+ occurred in 44% at 3 months, 50% at 6 months, 63% at 12 months, and 69% at 36 months. Cataract extraction surgery was performed in 15% of eyes post vitrectomy, 0% post scleral buckling, and 50% after both. The most common type of cataract to develop was nuclear sclerotic, which accounted for 61% of cataracts after vitrectomy, 50% after scleral buckling, and 50% after combined vitrectomy and scleral buckling. Scleral buckling surgery is associated with a low risk of cataract formation. Pars plana vitrectomy and combined vitrectomy and buckle have a higher risk of cataract development.

While the standard wind product (L2B) available operationally in near-real time from SeaWinds on QuikSCAT is only 25 km in resolution, QuikSCAT data can be enhanced to yield a 2.5 km ultra-high resolution (UHR) product. The latter can be used to help estimate Tropical Cyclone (TC) characteristics such as TC eye center and wind radii. Two studies are conducted in this thesis, in which QuikSCAT UHR wind product's effectiveness in estimating these TC characteristics is evaluated. First, a comparison is made between the analyst's choice of eye location based on UHR images and interpolated best-track position. In this analysis, the UHR images are divided into two categories, based on the analyst's confidence level of finding the eye center location. In each category, statistical error quantities are computed. UHR images within the high confidence category can provide, for a given year and basin, mean error distance as small as 19 km with a 10 km standard deviation. Second, a visual comparison of QuikSCAT's performance in estimating wind radii is made. QuikSCAT's performance is gauged against H*wind dataset and the Extended Best-Track (EBT) dataset. Results show that QuikSCAT UHR data yields a correct 34-kt wind radius most of the time regardless of the TC category when compared to both H*wind and EBT, whereas the 50- and 64-kt wind radii visual estimates do not always agree with H*wind and EBT. A more sophisticated method is also implemented to automatically estimate wind radii based on a model fit to QuikSCAT data. Results from this method are compared with EBT wind radii. Wind radii obtained from QuikSCAT model fit are generally highly correlated with EBT estimated wind radii. These two studies show that QuikSCAT UHR wind products are helpful in estimating TC eye location and wind radii, thus improving TC forecasting and analysis.

Ophthalmology is a branch of medicine that deals with the anatomy, physiology and diseases of the eyeball and orbit. An ophthalmic device for the acquirement and recognition of a human eye characteristics was created by researchers from Faculty of Information Technology. This device can be used either for biometric purposes or for medical purposes as a support diagnostic device. To achieve proper functionality, device must be able to adjust platform position in order to align optic camera with patient's eye.  The main focus of this thesis is to design and implement an algorithm for eye centre localisation based on images of the patient's face. The first part of this thesis describes general methods for eye localisation and proposed solution. To achieve requested accuracy, combination of multiple methods is used with adjusted parameters based on platform's features. The second part describes implementation of proposed solution as well as platform control. Multiple databases were used for training and testing of the algorithm. The third part summarises performed experiments. The proposed algorithm was implemented in the C++ language, using OpenCV library. Accuracy and speed of proposed algorithm are suitable for developed platform. In the end, the results are discussed and further improvements are proposed.

Ophthalmology is the branch of medicine that deals with the anatomy, physiology and diseases of the eyeball and orbit. An ophthalmic device for acquirement and recognition of human eye characteristics was created by researchers from Faculty of Information Technology. This device can be used either for biometric purposes or for medical purposes as a support diagnostic device. To achieve proper functionality, device must be able to adjust platform position in order to align optic camera with patient's eye.  The main focus of this work is to design and implement an algorithm for eye centre localisation based on images of the patient's face. The first part of this thesis describes general methods for eye localisation and proposed solution. To achieve desired accuracy, combination of multiple methods is used with adjusted parameters based on platform's features. The second part describes implementation of proposed solution as well as platform control. Multiple databases were used for training and testing of the algorithm and the third part summarises performed experiments. The proposed algorithm was implemented in the C++ language, using OpenCV library. Accuracy and speed of proposed algorithm are suitable for developed platform. In the end, the results are discussed and further improvements are proposed.