BACKGROUND We report necrotizing scleritis as a serious complication of a cosmetic eye whitening procedure that involves the use of intraoperative and postoperative topical mitomycin C. FINDINGS This is a single case report. A 59-year-old Caucasian male with a history of blepharitis status post uncomplicated LASIK refractive surgery reported chronic conjunctival hyperemia for 15 years prior t...

After reading this article, the reader should be able to: • describe the process of nightguard vital bleaching and discuss indications and contraindications. • list the situations amenable to at-home whitening, including extended bleaching times for tetracyclinestained teeth. • explain how to treat side effects, such as tooth sensitivity during whitening. • discuss treatment options for a singl...

AIM This study aimed to determine the efficacy of trays made with and without reservoirs, in conjunction with time and cost evaluations, by measuring color change with home whitening procedures. MATERIALS AND METHODS Extracted human maxillary teeth (central incisors n = 20; canines n = 20; molars n = 20) and 60 artificial teeth (lateral n = 20; premolar n = 40) were mounted into ten typodonts...

The main objective of this letter is to present an e cient algorithm for robust whitening in the presence of temporally uncorrelated additive noise that may be spatially correlated. This whitening is introduced as a pre-processing step in the blind source separation process. The robust whitening consists in the eigenvalue decomposition of a positive de nite linear combination of a set a correla...

Whitened Neural Network (WNN) is a recent advanced deep architecture, which improves convergence and generalization of canonical neural networks by whitening their internal hidden representation. However, the whitening transformation increases computation time. Unlike WNN that reduced runtime by performing whitening every thousand iterations, which degenerates convergence due to the ill conditi...

In natural image understanding, the whitening step plays an important role, especially within many unsupervised feature learning algorithms. Examples of these algorithms include ICA, TICA, Auto-encoder, and so forth. Current whitening techniques include Principal Component Analysis (PCA) and Zero-phase Component Analysis (ZCA). However, the drawbacks of these approaches are obvious: the time co...