5,141 research outputs found

    Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): Guidelines for medical 3D printing and appropriateness for clinical scenarios

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    Este número da revista Cadernos de Estudos Sociais estava em organização quando fomos colhidos pela morte do sociólogo Ernesto Laclau. Seu falecimento em 13 de abril de 2014 surpreendeu a todos, e particularmente ao editor Joanildo Burity, que foi seu orientando de doutorado na University of Essex, Inglaterra, e que recentemente o trouxe à Fundação Joaquim Nabuco para uma palestra, permitindo que muitos pudessem dialogar com um dos grandes intelectuais latinoamericanos contemporâneos. Assim, buscamos fazer uma homenagem ao sociólogo argentino publicando uma entrevista inédita concedida durante a sua passagem pelo Recife, em 2013, encerrando essa revista com uma sessão especial sobre a sua trajetória

    Multi-Modality Breast MRI Segmentation Using nn-UNet for Preoperative Planning of Robotic Surgery Navigation

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    Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling was used to segment the breast region. Then it was employed as an input for three-class labeling to segment fat, fibroglandular (FGT) tissues, and tumorous lesions. The first architecture has a 0.95 DCS, while the second has a 0.95, 0.83, and 0.41 for fat, FGT, and tumor classes, respectively

    Insights into 3D printing in medical applications

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    Three-dimensional (3D) printing has been increasingly used in the medical field with reported applications showing great value in assisting clinical decision-making and improving patient care (1-10). Patient-specific 3D printed models derived from medical imaging datasets, mainly from computed tomography (CT) and magnetic resonance imaging (MRI) are shown to play an important role in pre-surgical planning and simulation of complex surgical procedures, medical education and patient-doctor communication (1-14)

    A Computational Tool for Pre-operative Breast Augmentation Planning in Aesthetic Plastic Surgery

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    Abstract—Breast augmentation was the most commonly performed cosmetic surgery procedure in 2011 in the United States. Although aesthetically pleasing surgical results can only be achieved if the correct breast implant is selected from a large variety of different prosthesis sizes and shapes available on the market, surgeons still rely on visual assessment and other subjective approaches for operative planning because of lacking objective evaluation tools. In this paper we present the development of a software prototype for augmentation mammaplasty simulation solely based on 3D surface scans, from which patient-specific finite element models are generated in a semi-automatic process. The finite element model is used to pre-operatively simulate the expected breast shapes using physical soft tissue mechanics. Our approach uses a novel mechanism based on so-called displacement templates, which, for a specific implant shape and position, describe the respective internal body forces. Due to a highly efficient numerical solver we can provide immediate visual feedback of the simulation results, and thus the software prototype can be integrated smoothly into the medical workflow. The clinical value of the developed 3D computational tool for aesthetic breast augmentation surgery planning is demonstrated in patientspecific use cases
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