Aspectos clínicos do enxerto conjuntival 360° e do implante da membrana amniótica criopreservada no tratamento de úlceras de córnea em cães

To evaluate the clinical application of implant of the canine cryopreserved amniotic membrane (DMEM plus DMSO 1:1) and 360° conjunctival flap in the treatment of progressive corneal ulceration. 10 dogs of the different breeds, males and females, aging four months to four years old with deep corneal ulceration and different clinical progression were divided in two groups: G1=360° conjunctival graft (n=5) and G2=implant of amniotic membrane, sutured at the edge of the ulcer with epithelial side facing up, associated with the third eyelid flap (n=5). The comparative analysis between groups was: complications, blepharospasm, ocular secretion, corneal vascularization, epithelial defect and corneal opacification in six moments (first emergency care, surgery and 3, 7, 15 and 30 days of postoperative). Without epithelial defect was evaluated quality of the scar. It was used score scale for subjective to qualify of the ocular signs. In G1, it was observed the non-adherence of the conjunctival graft to the ulcer (n=2), dehiscence of the suture (n=2), anterior synechia (n=2) and intense chemosis (n=1). In G2, it was not observed these complications. It was not significant difference between the groups to others ocular parameters, but it was different among the start and end moments of the same groups (ocular secretion, corneal vascularization, epithelial defect). The corneal opacity was more intense in G1. According to the clinical results, the cryopreserved amniotic membrane implant proved to be as effective in the corneal ulceration in comparison to the 360° conjunctival flap, because probably, the membrane promoted a trophic support for epithelialization, anti-inflamatory effect associated with important to the end result phenotype.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.