Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

Cultivo de arroz irrigado orgânico no Rio Grande do Sul.

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Atividade inibitória de óleos fixos e essenciais no crescimento de isolados de Salmonella sp. e Salmonella typhimurium.

Neste trabalho foi avaliada a atividade antimicrobiana dos óleos essenciais de Cymbopogon wiinterianus, Pogostemon cablin, Ocimum basilicum, Ocimum gratissimum, Mentha arvensis, Eucalyptus spp., Ocimum basilicum var. Maria Bonita, Romarinus officinalis, Lippia sidoides, Cymbopogon citratus, Zingiber officinale, Azadirachta indica, Allium sativum contra Salmonella sp., e óleos de Pogostemon cablin, Ocimum basilicum var. Maria Bonita, Lippia sp., Lippia sidoides, Cymbopogon cytratus, Zingiber officinale e Ocimum gratissimum para Salmonella typhimurium

Multilocus sequence types of invasive Corynebacterium diphtheriae isolated in the Rio de Janeiro urban area, Brazil

Invasive infections caused by Corynebacterium diphtheriae in vaccinated and non-vaccinated individuals have been reported increasingly. In this study we used multilocus sequence typing (MLST) to study genetic relationships between six invasive strains of this bacterium isolated solely in the urban area of Rio de Janeiro, Brazil, during a 10-year period. Of note, all the strains rendered negative results in PCR reactions for the tox gene, and four strains presented an atypical sucrose-fermenting ability. Five strains represented new sequence types. MLST results did not support the hypothesis that invasive (sucrose-positive) strains of C. diphtheriae are part of a single clonal complex. Instead, one of the main findings of the study was that such strains can be normally found in clonal complexes with strains related to non-invasive disease. Comparative analyses with C. diphtheriae isolated in different countries provided further information on the geographical circulation of some sequence types

Processamento mínimo de mini beterraba.

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EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

Background: 3D reconstruction algorithms are of fundamental importance for augmented reality applications in computer-assisted surgery. However, few datasets of endoscopic stereo images with associated 3D surface references are currently openly available, preventing the proper validation of such algorithms. This work presents a new and rich dataset of endoscopic stereo images (EndoAbS dataset). Methods: The dataset includes (i) endoscopic stereo images of phantom abdominal organs, (ii) a 3D organ surface reference (RF) generated with a laser scanner and (iii) camera calibration parameters. A detailed description of the generation of the phantom and the camera–laser calibration method is also provided. Results: An estimation of the overall error in creation of the dataset is reported (camera–laser calibration error 0.43 mm) and the performance of a 3D reconstruction algorithm is evaluated using EndoAbS, resulting in an accuracy error in accordance with state-of-the-art results (<2 mm). Conclusions: The EndoAbS dataset contributes to an increase the number and variety of openly available datasets of surgical stereo images, including a highly accurate RF and different surgical conditions

Identificação e controle com antibióticos de bactérias endofíticas contaminantes em explantes de batata micropropagados.

Este trabalho teve por objetivos isolar, caracterizar e identificar bactérias endofíticas contaminantes encontradas em tecidos de batata durante a micropropagação e selecionar antibióticos para o controle in vitro desses microrganismos por meio da determinação da concentração bactericida mínima inibitória. Brotações de batata apresentando contaminação bacteriana durante a etapa de multiplicação in vitro, foram superficialmente esterilizadas e os internódios transferidos para placas de Petri com ágar nutriente, onde permaneceram incubadas a 28°C por até cinco dias. Após purificação, as bactérias foram caracterizadas e identificadas por testes taxonômicos. Um total de oito estirpes bacterianas foram isoladas e identificadas como pertencentes às famílias Acetobacteriaceae (1) e Enterobacteriaceae (2) e aos gêneros Corynebacterium (3), Pseudomonas (1) e Xanthomonas (1). Os melhores resultados para a inibição do crescimento bacteriano foram obtidos com os antibióticos ampicilina, cloranfenicol, estreptomicina e tetraciclina em concentrações que variaram de 32 a 256 mg L-1