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

Participação da Embrapa Solos em congressos: ano 2009.

bitstream/CNPS-2010/14826/1/doc119-2009-resumos-congressos.pd

Label-based Optimization of Dense Disparity Estimation for Robotic Single Incision Abdominal Surgery

Minimally invasive surgical techniques have led to novel approaches such as Single Incision Laparoscopic Surgery (SILS), which allows the reduction of post-operative infections and patient recovery time, improving surgical outcomes. However, the new techniques pose also new challenges to surgeons: during SILS, visualization of the surgical field is limited by the endoscope field of view, and the access to the target area is limited by the fact that instruments have to be inserted through a single port. In this context, intra-operative navigation and augmented reality based on pre-operative images have the potential to enhance SILS procedures by providing the information necessary to increase the intervention accuracy and safety. Problems arise when structures of interest change their pose or deform with respect to pre-operative planning, as usually happens in soft tissue abdominal surgery. This requires online estimation of the deformations to correct the pre-operative plan, which can be done, for example, through methods of depth estimation from stereo endoscopic images (3D reconstruction). The denser the reconstruction, the more accurate the deformation identification can be. This work presents an algorithm for 3D reconstruction of soft tissue, focusing on the refinement of the disparity map in order to obtain an accurate and dense point map. This algorithm is part of an assistive system for intra-operative guidance and safety supervision for robotic abdominal SILS . Results show that comparing our method with state-of-the-art CPU implementations, the percentage of valid pixel obtained with our method is 24% higher while providing comparable accuracy. Future research will focus on the development of a real-time implementation of the proposed algorithm, potentially based on a hybrid CPU-GPU processing framework

Virtual Assistive System for Robotic Single Incision Laparoscopic Surgery

Single Incision Laparoscopic Surgery (SILS) reduces the trauma of large wounds decreasing the post-operative infections, but introduces technical difficulties for the surgeon, who has to deal with at least three instruments in a single incision. These drawbacks can be overcome with the introduction of robotic arms inside the abdominal cavity, but still remain difficulties in the surgical field vision, limited by the endoscope field of view. This work is aimed at developing a system to improve the information required by the surgeon and enhance the vision during a robotic SILS. In the pre-operative phase, the segmentation and surface rendering of organs allow the surgeon to plan the surgery. During the intra-operative phase, the run-time information (tools and endoscope pose) and the pre-operative information (3D models of organs) are combined in a virtual environment. A point-based rigid registration of the virtual abdomen on the real patient creates a connection between reality and virtuality. The camera-image plane calibration allows to know at run-time the pose of the endoscopic view. The results show how using a small set of 4 points (the minimal number of points that would be used in a real procedure) for the camera-image plane calibration and for the registration between real and virtual model of the abdomen, is enough to provide a calibration/registration accuracy within the requirements

Coleção de culturas de microrganismos multifuncionais de clima temperado: manutenção, recuperação e viabilidade de fungos preservados em solo.

Resumo:228-1

Crescimento de Schinus terebinthifolius na região do baixo São Francisco.

Resumo

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