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Search Results: 1 - 10 of 10052 matches for " Jui-Ting Hsu "
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Computer-Assisted Navigation for Acetabular Cup Placement: a Single Image Guiding System
Jui-Ting Hsu,Ming-Tzu Tsai,Chih-Han Chang,Heng-Li Huang
Lecture Notes in Engineering and Computer Science , 2011,
Abstract:
Do Threaded Size and Surface Roughness Affect the Bone Stress and Bone-Implant Interfacial Sliding of Titanium Dental Implant?
Heng-Li Huang,Ming-Tzu Tsai,Jui-Ting Hsu,Lih-Jyh Fuh
Lecture Notes in Engineering and Computer Science , 2011,
Abstract:
A Novel Method of Estimating Dose Responses for Polymer Gels Using Texture Analysis of Scanning Electron Microscopy Images
Cheng-Ting Shih, Jui-Ting Hsu, Rou-Ping Han, Bor-Tsung Hsieh, Shu-Jun Chang, Jay Wu
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0067281
Abstract: Polymer gels are regarded as a potential dosimeter for independent validation of absorbed doses in clinical radiotherapy. Several imaging modalities have been used to convert radiation-induced polymerization to absorbed doses from a macro-scale viewpoint. This study developed a novel dose conversion mechanism by texture analysis of scanning electron microscopy (SEM) images. The modified N-isopropyl-acrylamide (NIPAM) gels were prepared under normoxic conditions, and were administered radiation doses from 5 to 20 Gy. After freeze drying, the gel samples were sliced for SEM scanning with 50×, 500×, and 3500× magnifications. Four texture indices were calculated based on the gray level co-occurrence matrix (GLCM). The results showed that entropy and homogeneity were more suitable than contrast and energy as dose indices for higher linearity and sensitivity of the dose response curves. After parameter optimization, an R2 value of 0.993 can be achieved for homogeneity using 500× magnified SEM images with 27 pixel offsets and no outlier exclusion. For dose verification, the percentage errors between the prescribed dose and the measured dose for 5, 10, 15, and 20 Gy were ?7.60%, 5.80%, 2.53%, and ?0.95%, respectively. We conclude that texture analysis can be applied to the SEM images of gel dosimeters to accurately convert micro-scale structural features to absorbed doses. The proposed method may extend the feasibility of applying gel dosimeters in the fields of diagnostic radiology and radiation protection.
Biological Characteristics of the MG-63 Human Osteosarcoma Cells on Composite Tantalum Carbide/Amorphous Carbon Films
Yin-Yu Chang, Heng-Li Huang, Ya-Chi Chen, Jui-Ting Hsu, Tzong-Ming Shieh, Ming-Tzu Tsai
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0095590
Abstract: Tantalum (Ta) is a promising metal for biomedical implants or implant coating for orthopedic and dental applications because of its excellent corrosion resistance, fracture toughness, and biocompatibility. This study synthesizes biocompatible tantalum carbide (TaC) and TaC/amorphous carbon (a-C) coatings with different carbon contents by using a twin-gun magnetron sputtering system to improve their biological properties and explore potential surgical implant or device applications. The carbon content in the deposited coatings was regulated by controlling the magnetron power ratio of the pure graphite and Ta cathodes. The deposited TaC and TaC/a-C coatings exhibited better cell viability of human osteosarcoma cell line MG-63 than the uncoated Ti and Ta-coated samples. Inverted optical and confocal imaging was used to demonstrate the cell adhesion, distribution, and proliferation of each sample at different time points during the whole culture period. The results show that the TaC/a-C coating, which contained two metastable phases (TaC and a-C), was more biocompatible with MG-63 cells compared to the pure Ta coating. This suggests that the TaC/a-C coatings exhibit a better biocompatible performance for MG-63 cells, and they may improve implant osseointegration in clinics.
Predicting Cortical Bone Strength from DXA and Dental Cone-Beam CT
Jui-Ting Hsu, Ying-Ju Chen, Ming-Tzu Tsai, Howard Haw-Chang Lan, Fu-Chou Cheng, Michael Y. C. Chen, Shun-Ping Wang
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0050008
Abstract: Objective This study compared the capabilities of dual-energy X-ray absorptiometry (DXA) and dental cone-beam computed tomography (CBCT) for predicting the cortical bone strength of rat femurs and tibias. Materials and Methods Specimens of femurs and tibias obtained from 14 rats were first scanned with DXA to obtain the areal bone mineral density (BMD) of the midshaft cortical portion of the bones. The bones were then scanned using dental CBCT to measure the volumetric cortical bone mineral density (vCtBMD) and the cross-sectional moment of inertia (CSMI) for calculating the bone strength index (BSI). A three-point bending test was conducted to measure the fracture load of each femur and tibia. Bivariate linear Pearson analysis was used to calculate the correlation coefficients (r values) among the CBCT measurements, DXA measurements, and three-point bending parameters. Results The correlation coefficients for the associations of the fracture load with areal BMD (measured using DXA), vCtBMD (measured using CBCT), CSMI (measured using CBCT), and BSI were 0.585 (p = 0.028) and 0.532 (p = 0.050) (for the femur and tibia, respectively), 0.638 (p = 0.014) and 0.762 (p = 0.002), 0.778 (p = 0.001) and 0.792 (p<0.001), and 0.822 (p<0.001) and 0.842 (p<0.001), respectively. Conclusions CBCT was found to be superior to DXA for predicting cortical bone fracture loads in rat femurs and tibias. The BSI, which is a combined index of densitometric and geometric parameters, was especially useful. Further clinical studies are needed to validate the predictive value of BSI obtained from CBCT and should include testing on human cadaver specimens.
Analyses of Antibacterial Activity and Cell Compatibility of Titanium Coated with a Zr–C–N Film
Yin-Yu Chang, Heng-Li Huang, Chih-Ho Lai, Jui-Ting Hsu, Tzong-Ming Shieh, Aaron Yu-Jen Wu, Chao-Ling Chen
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0056771
Abstract: Objective The purpose of this study was to verify the antibacterial performance and cell proliferation activity of zirconium (Zr)–carbon (C)–nitride (N) coatings on commercially pure titanium (Ti) with different C contents. Materials and Methods Reactive nitrogen gas (N2) with and without acetylene (C2H2) was activated by Zr plasma in a cathodic-arc evaporation system to deposit either a zirconium nitride (ZrN) or a Zr–C–N coating onto Ti plates. The bacterial activity of the coatings was evaluated against Staphylococcus aureus with the aid of SYTO9 nucleic acid staining and scanning electron microscopy (SEM). Cell compatibility, mRNA expression, and morphology related to human gingival fibroblasts (HGFs) on the coated samples were also determined by using the MTT assay, reverse transcriptase–polymerase chain reaction, and SEM. Results The Zr–C–N coating with the highest C content (21.7 at%) exhibited the lowest bacterial preservation (P<0.001). Biological responses including proliferation, gene expression, and attachment of HGF cells to ZrN and Zr–C–N coatings were comparable to those of the uncoated Ti plate. Conclusions High-C-content Zr–C–N coatings not only provide short-term antibacterial activity against S. aureus but are also biocompatible with HGF cells.
Location of the Mandibular Canal and Thickness of the Occlusal Cortical Bone at Dental Implant Sites in the Lower Second Premolar and First Molar
Jui-Ting Hsu,Heng-Li Huang,Lih-Jyh Fuh,Rou-Wei Li,Jay Wu,Ming-Tzu Tsai,Yen-Wen Shen,Ming-Gene Tu
Computational and Mathematical Methods in Medicine , 2013, DOI: 10.1155/2013/608570
Abstract: The objective of this study was to evaluate the location of the mandibular canal and the thickness of the occlusal cortical bone at dental implant sites in the lower second premolar and lower first molar by using dental cone-beam computed tomography (CBCT). Seventy-nine sites (47 second premolar and 32 first molar sites) were identified in the dental CBCT examinations of 47 patients. In this study, 4 parameters were measured: (1) MC—the distance from the mandibular canal to the upper border of the mandible; (2) CD—the distance from the mandibular canal to the buccal border of the mandible; (3) MD—the distance from the mandibular canal to the lingual border of the mandible; (4) TC—the thickness of the cortical bone at the occlusal side. A statistical analysis was employed to compare the size and differences between these 4 parameters at the lower second premolar and lower first molar. Regarding the MC and MD, the experimental results showed no statistical difference between the first molar and second premolar. However, the TC for the second premolar was greater than that of the first molar. Thus, careful consideration is necessary in choosing the size of and operation type for dental implants. 1. Introduction The location of the mandibular canal is a critical factor that can influence dental implant surgery [1–5]. Dental implant surgery demonstrates a 6.5%–37% incidence of temporary or permanent paralysis, or even sensory loss, because of inferior alveolar nerve damage in the mandibular canal resulting from the poor assessment of bone length and the subsequent use of implant bodies of excessive lengths [2, 3, 6–8]. Therefore, to avoid damage, it is crucial to properly assess the mandibular canal location in the mandible before dental implant procedures. In addition to dental implant surgery, the inferior alveolar nerve may also be damaged by osteotomies or fracture repair; thus, a strong understanding of the intrabony anatomy of the mandibular canal is required before conducting dental implant surgery or operative procedures (e.g., sagittal split osteotomies or placement of cortical fixation screws). Furthermore, the cortical bone thickness of the alveolar bone at the implant site is a critical factor affecting the success of dental implant surgery, because the primary stability of the implant body insertion in the alveolar bone increases with the thickness of the cortical bone [9–13]. Superior osseointegration enhances the long-term survival rate of the implant body. Although the location of the mandibular canal in the mandible can be precisely
A Smart Green Building: An Environmental Health Control Design
Shang-Yuan Chen,Jui-Ting Huang
Energies , 2012, DOI: 10.3390/en5051648
Abstract: This study proposes the establishment of an environmental health information management platform providing residential users with a comfortable, healthy indoor environment. Taking the S House as an example, the study: (1) assigned environmental health performance indicators, (2) established constraints to maintain environmental conditions, and (3) provided optimized management control mechanisms and methods. The environmental health information management platform provides an optimized control and solution pathway ensuring the quality of the indoor health environment and equipment energy conservation.
Vehicular Testbeds - Model Validation before Large Scale Deployment
Mario Gerla,Jui-Ting Weng,Eugenio Giordano,Giovanni Pau
Journal of Communications , 2012, DOI: 10.4304/jcm.7.6.451-457
Abstract: Vehicular communications are becoming a reality due to the investments by stakeholders like car manufacturers and Public Transport Authorities. The building blocks of the ”Vehicle Grid” (radios, Access Points, spectrum, standards, etc.) are coming into place enabling a broad gamut of applications that range from navigation safety, intelligent transport, entertainment and urban sensing. Vehicular protocols and applications, however, must be carefully tested before deployment in the urban grid and introduction to the users. This validation must be carried out progressively in simulation, emulation and small scale testbed environments. In this paper we discuss the important role of the vehicular testbed in validating models and protocols before deployment in large scale scenarios. We illustrate the concept using two case studies that were carried out in the UCLA open vehicular testbed.
Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks
Dong Yu,Michael L. Seltzer,Jinyu Li,Jui-Ting Huang,Frank Seide
Computer Science , 2013,
Abstract: Recent studies have shown that deep neural networks (DNNs) perform significantly better than shallow networks and Gaussian mixture models (GMMs) on large vocabulary speech recognition tasks. In this paper, we argue that the improved accuracy achieved by the DNNs is the result of their ability to extract discriminative internal representations that are robust to the many sources of variability in speech signals. We show that these representations become increasingly insensitive to small perturbations in the input with increasing network depth, which leads to better speech recognition performance with deeper networks. We also show that DNNs cannot extrapolate to test samples that are substantially different from the training examples. If the training data are sufficiently representative, however, internal features learned by the DNN are relatively stable with respect to speaker differences, bandwidth differences, and environment distortion. This enables DNN-based recognizers to perform as well or better than state-of-the-art systems based on GMMs or shallow networks without the need for explicit model adaptation or feature normalization.
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