Yazar "Zeybek, Mustafa." seçeneğine göre listele

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    Assessment of changes in masseter muscle by three-dimensional close-range photogrammetry after Botulinum toxin type-A injection: A case report with review of literature
    (PAKISTAN MEDICAL ASSOC, 2019) Bayrak, Nagehan Burcu.; Zeybek, Mustafa.; Sanlioglu, Ismail.; Dolanmaz, Dogan.
    Masseter muscle hypertrophy (MMH) is a benign, unilateral or bilateral, painless enlargement. Treatment protocols include surgical excision or a non-invasive option, using botulinum toxin type A (BTX-A). There is no study in the literature that measures this dimensional change in the masseter muscle (MM). The aim of this case report is to present changes in volume and surface area in MM with three-dimensional close-range stereophotogrammetry (3DCS). For treatment 30 units of BTX-A was injected into the three points hypertrophic muscle and patient records were taken to compare with 3DCS with a non-metric Canon EOS 550 D camera before and after injection. The changes in the surface area and volume of this muscle were mapped and the objective data were obtained. This technique is useful for predicting the results of BTX-A application, and can be a useful tool for better physician-patient communication.
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    Point cloud filtering on UAV based point cloud
    (ELSEVIER SCI LTD, 2019) Zeybek, Mustafa.; Şanlıoğlu, İsmail.
    Nowadays, Unmanned Aerial Vehicles (UAVs) have been attracted wide attentions such as a new measurement equipment and mapping, which are capable of the high-resolution point cloud data collection. In addition, a massive point cloud data has brought about the data filtering and irregular data organization for the generation of digital terrain models. Filtering of point clouds contains vegetations and artificial objects play a crucial role for bare earth terrain modelling. Topographical maps rely on the data structures which are built on bare ground terrain points. The bare earth surface extraction is not the only crucial to the topographical maps but also decision-making processes such as natural hazards management, deformation analysis and interpretation. In order to filter a UAV-based 3D raw point cloud data, in this paper, filtering performance of four different algorithms using open source and commercial software's have been investigated, (1) curvature based (Multiscale Curvature Classification-MCC), (2) surface-based filtering (FUSION), (3) progressive TIN based (LasTool-LasGround module-commercial) and (4) physical simulation processing (Cloth Simulation Filtering-CSF). The applied filtering results were validated with the reference data set classified by operator. Although different filtering methodologies implemented on point clouds, these methods demonstrated similar results to extract ground on distinctive terrain feature such as dense vegetated, flat surface, rough and complex landscapes. The filtering algorithms' results revealed that UAV-generated data suitable for extraction of bare earth surface feature on the different type of a terrain. Accuracy of the filtered point cloud reached the 93% true classification on flat surfaces from CSF filtering method. (C) 2018 Elsevier Ltd. All rights reserved.