Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

All Green, But Equal? Morphological Traits And Ecological Implications On Spores Of Three Species Of Mosses In The Brazilian Atlantic Forest.

Spores of the tropical mosses Pyrrhobryum spiniforme, Neckeropsis undulata and N. disticha were characterized regarding size, number per capsule and viability. Chemical substances were analyzed for P. spiniforme and N. undulata spores. Length of sporophyte seta (spore dispersal ability) was analyzed for P. spiniforme. Four to six colonies per species in each site (lowland and highland areas of an Atlantic Forest; Serra do Mar State Park, Brazil) were visited for the collection of capsules (2008 - 2009). Neckeropsis undulata in the highland area produced the largest spores (ca. 19 µm) with the highest viability. The smallest spores were found in N. disticha in the lowland (ca. 13 µm). Pyrrhobryum spiniforme produced more spores per capsule in the highland (ca. 150,000) than in lowland (ca. 40,000); longer sporophytic setae in the lowland (ca. 64 mm) than in the highland (ca. 43 mm); and similar sized spores in both areas (ca. 16 µm). Spores of N. undulata and P. spiniforme contained lipids and proteins in the cytoplasm, and acid/neutral lipids and pectins in the wall. Lipid bodies were larger in N. undulata than in P. spiniforme. No starch was recorded for spores. Pyrrhobryum spiniforme in the highland area, different from lowland, was characterized by low reproductive effort, but presented many spores per capsule.

Esporte e clube sócio-esportivo : percurso, contextos e perspectivas a partir de um estudo de caso em clube esportivo espanhol

Universidade Estadual de Campinas . Faculdade de Educação Física

Estudo de aplicação de rede de investigação em saude e urgencia em educação fisica

Universidade Estadual de Campinas. Faculdade de Educação Física