284 research outputs found

    ToothInpaintor: Tooth Inpainting from Partial 3D Dental Model and 2D Panoramic Image

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    In orthodontic treatment, a full tooth model consisting of both the crown and root is indispensable in making the treatment plan. However, acquiring tooth root information to obtain the full tooth model from CBCT images is sometimes restricted due to the massive radiation of CBCT scanning. Thus, reconstructing the full tooth shape from the ready-to-use input, e.g., the partial intra-oral scan and the 2D panoramic image, is an applicable and valuable solution. In this paper, we propose a neural network, called ToothInpaintor, that takes as input a partial 3D dental model and a 2D panoramic image and reconstructs the full tooth model with high-quality root(s). Technically, we utilize the implicit representation for both the 3D and 2D inputs, and learn a latent space of the full tooth shapes. At test time, given an input, we successfully project it to the learned latent space via neural optimization to obtain the full tooth model conditioned on the input. To help find the robust projection, a novel adversarial learning module is exploited in our pipeline. We extensively evaluate our method on a dataset collected from real-world clinics. The evaluation, comparison, and comprehensive ablation studies demonstrate that our approach produces accurate complete tooth models robustly and outperforms the state-of-the-art methods

    Optimal Control of Sweeping Processes in Robotics and Traffic Flow Models

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    The paper is mostly devoted to applications of a novel optimal control theory for perturbed sweeping/Moreau processes to two practical dynamical models. The first model addresses mobile robot dynamics with obstacles, and the second one concerns control and optimization of traffic flows. Describing these models as controlled sweeping processes with pointwise/hard control and state constraints and applying new necessary optimality conditions for such systems allow us to develop efficient procedures to solve naturally formulated optimal control problems for the models under consideration and completely calculate optimal solutions in particular situations

    Evaluation of Growth Simulators for Forest Management in Terms of Functionality and Software Structure Using AHP

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    A range of computer models exist for simulating forest growth, with different model functions, spatial resolutions and regional calibration specifications. Choosing a suitable simulator is difficult due to its abundance and complexity. The aim of the project is to evaluate a simulator that could be adapted to conditions in Switzerland and used to support decision‐making processes in both forest enterprises and scientific contexts. Fourteen potentially suitable forest growth simulators were identified through a literature review, which was then narrowed down to four: BWINPro, SILVA, MOSES and PrognAus. In the second phase, these were systematically evaluated in terms of functionality and software structure using AHP, in order to identify a suitable simulator. The AHP evaluation entailed: (1) determining the decision criteria and hierarchy, (2) performing pairwise comparisons and calculating the utility values and (3) conducting a sensitivity analysis. AHP was found to provide a transparent, verifiable evaluation process for simulator selection. This enabled a critical argumentation and assessment of the simulators. In the third phase, not covered by this article, the selected simulator will be parametrised for Swiss conditions and incorporated into an overarching decision‐support system for forest planning and management

    エンチ アタリ ノ ヨウリョウ ガ ヒトシイ ジョウケンカ ニオケル ジュハバ ト ジュコウ ノ チガイ ガ カジュエン ノ ヒカリ カンキョウ ニ オヨボス エイキョウ : ジュカン セッケイ システム (CDS) オ モチイタ モデル ジッケン

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    In order to investigate the effects of tree width or tree height on orchard light environment where the foliage biomass per orchard land area was equal, the following model experiments were done. Using four kinds of tree widths, three kinds of tree heights and various alternatives in the training- pruning procedures, the next ten crown model groups (CMGs) were designed by the CDS method (Yamamoto, 2020), viz., thick type and medium height(CMG1), thick type and short height(CMG2), slender type and medium height(CMG3), slender type and short height(CMG4), ultraslender type and medium height(CMG5), ultraslender type and short height(CMG6), thin hedgerow type and medium height(CMG7), thin hedgerow type and short height(CMG8), ultrathick type and medium height(CMG9)and ultrathick type and long height(CMG10). A sort of green road with an applicable width was given to each CMG. Sum total 46,080 crown models were designed. The total number of crown models was 9,591, which satisfied the five restrictions, i.e. the tree height, the east-west tree width, the north-south tree width, the upper limit of leafy blocks number per tree and the lower limit. Orchard light environment, photosynthesis and characteristics of canopy shape were analyzed on these crown models using the same methods as described in the previous reports (Yamamoto, 2015, 2016). As the result, great differences in the light environment were found between the crown model groups. For example in the experiment plot of four primary scaffold branches (PSBs), by comparing CDMPPFD (the daily mean of leaf PPFD on a clear day) between the ten CMGs, the next relationship of the mean CDMPPFD were found as follow; CMG3≥ CMG4≥ CMG6> CMG8> CMG7≥ CMG5> CMG1≥ CMG9≥ CMG2> CMG10. There was the close correspondence between the order of the mean CDMPPFD and that of the characteristics of canopy shape. The causes were considered that the proportion of the leaf layers at crown surface more increases and the shades inside the crown more decreases as the crown becomes thinner. The mean CDMPPFD of five crown models were compared, whose CDMPPFD was the highest to the fifth in each crown model. When the mean CDMPPFD of CMG1 was 100, the relative value of CMG6 was over about 140, that of CMG3 and CMG4 were over about 138, and that of CMG7 and CMG8 were over about 134. On the contrary, the relative values in CMG2, CMG9 and CMG10 were under about 100. However, the large effect of the tree height on the CDMPPFD could not be recognized in many crown model groups except of cases between MG5 and CMG6

    Geometrical modeling of complete dental shapes by using panoramic X-ray, digital mouth data and anatomical templates

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    In the field of orthodontic planning, the creation of a complete digital dental model to simulate and predict treatments is of utmost importance. Nowadays, orthodontists use panoramic radiographs (PAN) and dental crown representations obtained by optical scanning. However, these data do not contain any 3D information regarding tooth root geometries. A reliable orthodontic treatment should instead take into account entire geometrical models of dental shapes in order to better predict tooth movements. This paper presents a methodology to create complete 3D patient dental anatomies by combining digital mouth models and panoramic radiographs. The modeling process is based on using crown surfaces, reconstructed by optical scanning, and root geometries, obtained by adapting anatomical CAD templates over patient specific information extracted from radiographic data. The radiographic process is virtually replicated on crown digital geometries through the Discrete Radon Transform (DRT). The resulting virtual PAN image is used to integrate the actual radiographic data and the digital mouth model. This procedure provides the root references on the 3D digital crown models, which guide a shape adjustment of the dental CAD templates. The entire geometrical models are finally created by merging dental crowns, captured by optical scanning, and root geometries, obtained from the CAD templates

    Creation of 3D Multi-Body Orthodontic Models by Using Independent Imaging Sensors

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    In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients’ mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning
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