scholarly journals Automatic Tooth Segmentation of Dental Mesh Based on Harmonic Fields

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Sheng-hui Liao ◽  
Shi-jian Liu ◽  
Bei-ji Zou ◽  
Xi Ding ◽  
Ye Liang ◽  
...  
Keyword(s):  
State Of The Art ◽  
A Priori ◽  
Mesh Segmentation ◽  
High Quality ◽  
Harmonic Field ◽  
Segmentation Methods ◽  
Dental Models ◽  
Different Shapes ◽  
Fully Automatic ◽  
Segmentation Framework

An important preprocess in computer-aided orthodontics is to segment teeth from the dental models accurately, which should involve manual interactions as few as possible. But fully automatic partition of all teeth is not a trivial task, since teeth occur in different shapes and their arrangements vary substantially from one individual to another. The difficulty is exacerbated when severe teeth malocclusion and crowding problems occur, which is a common occurrence in clinical cases. Most published methods in this area either are inaccurate or require lots of manual interactions. Motivated by the state-of-the-art general mesh segmentation methods that adopted the theory of harmonic field to detect partition boundaries, this paper proposes a novel, dental-targeted segmentation framework for dental meshes. With a specially designed weighting scheme and a strategy of a priori knowledge to guide the assignment of harmonic constraints, this method can identify teeth partition boundaries effectively. Extensive experiments and quantitative analysis demonstrate that the proposed method is able to partition high-quality teeth automatically with robustness and efficiency.

Використання автоматичної сегментації з допомогою гармонічного поля для розпізнавання образу зубів у щелепі

2020 ◽  
pp. 93-99
Author(s):  
Михайло Войченко ◽  
◽  
Василь Татарин ◽  
Keyword(s):  
3D Model ◽  
A Priori ◽  
A Priori Knowledge ◽  
Mesh Segmentation ◽  
Harmonic Field ◽  
Knowledge Strategy ◽  
Priori Knowledge

An important preliminary procedure in automated orthodontics is the precise segmentation of the teeth from the 3D model of the jaw, which should include as few manual operations as possible. Motivated by ultramodern general methods of mesh segmentation, which have adopted the theory of harmonic field to identify segments, this article investigates a new, aimed at dentistry structure of dental mesh segmentation. Thanks to a specially designed weighing scheme and a priori knowledge strategy for managing harmonic constraints, this method can effectively determine the boundaries of the teeth.

scholarly journals Automatic Comic Generation with Stylistic Multi-page Layouts and Emotion-driven Text Balloon Generation

2021 ◽  
Vol 17 (2) ◽  
pp. 1-19
Author(s):  
Xin Yang ◽  
Zongliang Ma ◽  
Letian Yu ◽  
Ying Cao ◽  
Baocai Yin ◽  
...  
Keyword(s):  
Automatic System ◽  
State Of The Art ◽  
User Studies ◽  
High Quality ◽  
Page Layout ◽  
Reading Experience ◽  
Different Types ◽  
Fully Automatic ◽  
Speaker Detection ◽  
The Rich

In this article, we propose a fully automatic system for generating comic books from videos without any human intervention. Given an input video along with its subtitles, our approach first extracts informative keyframes by analyzing the subtitles and stylizes keyframes into comic-style images. Then, we propose a novel automatic multi-page layout framework that can allocate the images across multiple pages and synthesize visually interesting layouts based on the rich semantics of the images (e.g., importance and inter-image relation). Finally, as opposed to using the same type of balloon as in previous works, we propose an emotion-aware balloon generation method to create different types of word balloons by analyzing the emotion of subtitles and audio. Our method is able to vary balloon shapes and word sizes in balloons in response to different emotions, leading to more enriched reading experience. Once the balloons are generated, they are placed adjacent to their corresponding speakers via speaker detection. Our results show that our method, without requiring any user inputs, can generate high-quality comic pages with visually rich layouts and balloons. Our user studies also demonstrate that users prefer our generated results over those by state-of-the-art comic generation systems.

Research on CT Image Segmentation of Computer-Aided Liver Operation

2014 ◽  
Vol 513-517 ◽  
pp. 3115-3121
Author(s):  
Yun Tao Wei ◽  
Yi Bing Zhou
Keyword(s):  
A Priori ◽  
Liver Segmentation ◽  
Segmentation Methods ◽  
Pros And Cons ◽  
Automatic Methods ◽  
Fully Automatic ◽  
Ct Data ◽  
Liver Region ◽  
The Comparative Study ◽  
Threshold Process

The segmentation of liver using computed tomography (CT) data has gained a lot of importance in the medical image processing field. In this paper, we present a survey on liver segmentation methods and techniques using CT images for liver segmentation. Generally, liver segmentation methods are divided into two main classes, semi-automatic and fully automatic methods, under each of these two categories, several methods, approaches, related issues and problems will be defined and explained. The evaluation measurements and scoring for the liver segmentation are shown, followed by the comparative study for liver segmentation methods, pros and cons of methods will be accentuated carefully. Here a fully 3D algorithm for automatic liver segmentation from CT volumetric datasets is presented. The algorithmstarts by smoothing the original volume using anisotropic diffusion. The coarse liver region is obtained from the threshold process that is based on a priori knowledge.

Building Attention and Edge Convolution Neural Networks for Bioactivity and Physical-Chemical Property Prediction

2019 ◽  
Author(s):  
Michael Withnall ◽  
Edvard Lindelöf ◽  
Ola Engkvist ◽  
Hongming Chen
Keyword(s):  
Message Passing ◽  
State Of The Art ◽  
A Priori ◽  
Model Performance ◽  
Learning Approaches ◽  
Physical Chemical ◽  
Chemical Descriptor ◽  
Derived Properties ◽  
Memory Schemes ◽  
Hyperparameter Selection

We introduce Attention and Edge Memory schemes to the existing Message Passing Neural Network framework for graph convolution, and benchmark our approaches against eight different physical-chemical and bioactivity datasets from the literature. We remove the need to introduce <i>a priori</i> knowledge of the task and chemical descriptor calculation by using only fundamental graph-derived properties. Our results consistently perform on-par with other state-of-the-art machine learning approaches, and set a new standard on sparse multi-task virtual screening targets. We also investigate model performance as a function of dataset preprocessing, and make some suggestions regarding hyperparameter selection.

The Formability and Elongation of Aluminum Alloys AA5083 and AA3003 for Micro-Truss Sandwiches Manufacturing

2020 ◽  
Vol 38 (9A) ◽  
pp. 1396-1405
Author(s):  
Arwa F. Tawfeeq ◽  
Matthew R. Barnett
Keyword(s):  
Aluminum Alloy ◽  
Strain Rate ◽  
Cost Effective ◽  
Tensile Tests ◽  
Truss Structures ◽  
High Quality ◽  
Trade Off ◽  
Clad Layer ◽  
Higher Temperature ◽  
Different Shapes

The development in the manufacturing of micro-truss structures has demonstrated the effectiveness of brazing for assembling these sandwiches, which opens new opportunities for cost-effective and high-quality truss manufacturing. An evolving idea in micro-truss manufacturing is the possibility of forming these structures in different shapes with the aid of elevated temperature. This work investigates the formability and elongation of aluminum alloy sheets typically used for micro-truss manufacturing, namely AA5083 and AA3003. Tensile tests were performed at a temperature in the range of 25-500 ○C and strain rate in the range of 2x10-4 -10-2 s-1. The results showed that the clad layer in AA3003 exhibited an insignificant effect on the formability and elongation of AA3003. The formability of the two alloys was improved significantly with values of m as high as 0.4 and 0.13 for AA5083 and AA3003 at 500 °C. While the elongation of both AA5083 and AA3003 was improved at a higher temperature, the elongation of AA5083 was inversely related to strain rate. It was concluded that the higher the temperature is the better the formability and elongation of the two alloys but at the expense of work hardening. This suggests a trade-off situation between formability and strength. 

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

scholarly journals Distinguishing Adenocarcinomas from Granulomas in the CT scan of the chest: performance degradation evaluation in the automatic segmentation framework

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mahsa Bank Tavakoli ◽  
Mahdi Orooji ◽  
Mehdi Teimouri ◽  
Ramita Shahabifar
Keyword(s):  
State Of The Art ◽  
Automatic Segmentation ◽  
Texture Features ◽  
Standards Of Care ◽  
Shape Features ◽  
Selection Methods ◽  
Segmentation Framework ◽  
Vessel Tortuosity ◽  
Benign Nodules ◽  
Degradation Evaluation

Abstract Objective The most common histopathologic malignant and benign nodules are Adenocarcinoma and Granuloma, respectively, which have different standards of care. In this paper, we propose an automatic framework for the diagnosis of the Adenocarcinomas and the Granulomas in the CT scans of the chest from a private dataset. We use the radiomic features of the nodules and the attached vessel tortuosity for the diagnosis. The private dataset includes 22 CTs for each nodule type, i.e., adenocarcinoma and granuloma. The dataset contains the CTs of the non-smoker patients who are between 30 and 60 years old. To automatically segment the delineated nodule area and the attached vessels area, we apply a morphological-based approach. For distinguishing the malignancy of the segmented nodule, two texture features of the nodule, the curvature Mean and the number of the attached vessels are extracted. Results We compare our framework with the state-of-the-art feature selection methods for differentiating Adenocarcinomas from Granulomas. These methods employ only the shape features of the nodule, the texture features of the nodule, or the torsion features of the attached vessels along with the radiomic features of the nodule. The accuracy of our framework is improved by considering the four selected features.

scholarly journals Global optimization of an encapsulated Si/SiO$$_2$$ L3 cavity with a 43 million quality factor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. P. Vasco ◽  
V. Savona
Keyword(s):  
Global Optimization ◽  
Photonic Crystal ◽  
Quality Factor ◽  
State Of The Art ◽  
Optimization Strategy ◽  
High Quality ◽  
Optimal Value ◽  
Out Of Plane ◽  
Fabrication Tolerances ◽  
Structural Imperfections

AbstractWe optimize a silica-encapsulated silicon L3 photonic crystal cavity for ultra-high quality factor by means of a global optimization strategy, where the closest holes surrounding the cavity are varied to minimize out-of-plane losses. We find an optimal value of $$Q_c=4.33\times 10^7$$ Q c = 4.33 × 10 7 , which is predicted to be in the 2 million regime in presence of structural imperfections compatible with state-of-the-art silicon fabrication tolerances.

scholarly journals An All-Batch Loss for Constructing Prediction Intervals

2021 ◽  
Vol 11 (4) ◽  
pp. 1728
Author(s):  
Hua Zhong ◽  
Li Xu
Keyword(s):  
Gradient Descent ◽  
State Of The Art ◽  
Prediction Interval ◽  
Feedforward Neural Networks ◽  
Important Research ◽  
Likelihood Principle ◽  
High Quality ◽  
Construction Methods ◽  
Important Research Topic ◽  
Benchmark Datasets

The prediction interval (PI) is an important research topic in reliability analyses and decision support systems. Data size and computation costs are two of the issues which may hamper the construction of PIs. This paper proposes an all-batch (AB) loss function for constructing high quality PIs. Taking the full advantage of the likelihood principle, the proposed loss makes it possible to train PI generation models using the gradient descent (GD) method for both small and large batches of samples. With the structure of dual feedforward neural networks (FNNs), a high-quality PI generation framework is introduced, which can be adapted to a variety of problems including regression analysis. Numerical experiments were conducted on the benchmark datasets; the results show that higher-quality PIs were achieved using the proposed scheme. Its reliability and stability were also verified in comparison with various state-of-the-art PI construction methods.

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