Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

Global Exponential Stability of Hybrid Non-autonomous Neural Networks with Markovian Switching

Neural Processing Letters - This paper discusses the global exponential stability for a class of hybrid non-autonomous neural networks (HNNNs) with Markovian switching, which includes the factors...     

Anchoring single Pt atoms on hollow Ag3VO4 spheres for improved activity towards photocatalytic H2 evolution reaction

The high cost of noble metal catalysts has been a great bottleneck for the catalyst industry. Using the noble metal at a single-atom level for catalytic applications could dramatically decrease the cost. The impacts of single Pt atoms on the photocatalytic performance of Ag₃VO₄ have been investigated and reported. In this report, single Pt atoms were anchored on the surface of Ag₃VO₄ (AVO) as a cocatalyst, and the resultant composite photocatalyst has been studied for photocatalytic H₂ production from water driven by visible light. The as-prepared AVO particles are hollow nanospheres in the monoclinic phase with a bandgap of 2.20 eV. The light absorption edge of AVO/Pt is slightly red-shifted compared to that of the pristine AVO, indicating more visible light absorption of AVO/Pt. The XPS peaks of Ag, V, and Pt exhibit a significant shift after AVO and Pt get into contact, suggesting the strong interaction between the surface Ag and V atoms, and single Pt atoms. After 3-h illumination, the photocatalytic H₂ evolution amount from AVO/Pt is improved up to 1400 μmol, which is 2.8 times that on the bare AVO. Such efficient photocatalytic H₂ evolution on AVO/Pt is still maintained after five reaction cycles. The better photocatalytic performance of AVO/Pt has been attributed to the more efficient visible light utilization and the lower interfacial charge transfer resistance, as demonstrated in the DRS and EIS spectra. The presence of the surface Pt atoms also leads to a higher amount of reactive radicals, which could efficiently promote the surface redox reactions.     

A dynamic SVR–ARMA model with improved fruit fly algorithm for the nonlinear fiber stretching process

Natural Computing - The fiber stretching process plays the key role in the process of fiber production and its effects is measured by the stretching ratio. The stretching ratio is determined by the...     

Optimal Spectral-Galerkin Methods Using Generalized Jacobi Polynomials

We extend the definition of the classical Jacobi polynomials withindexes α, β>−1 to allow α and/or β to be negative integers. We show that the generalized Jacobi polynomials, with indexes corresponding to the number of boundary conditions in a given partial differential equation, are the natural basis functions for the spectral approximation of this partial differential equation. Moreover, the use of generalized Jacobi polynomials leads to much simplified analysis, more precise error estimates and well conditioned algorithms.Mathematics subject classification 1991. 65N35, 65N22, 65F05, 35J05     

Experimental and modeling approaches of MR behaviors under large step strains

Rheological properties of MR fluids under large step strain shear are presented in this paper. The experiments were carried out using a rheometer with parallel-plate geometry. Under the large step strain shear, MR fluids behave as nonlinear viscoelastic properties, where the stress relaxation modulus, G(t, γ), shows a decreasing trend with step strain. The experimental results indicate that G(t, γ) obeys time-strain separability. Thus, a mathematical form based on finite exponential serials is proposed to predict MR behavior. In this model, G(t, γ) is represented as the product of a linear stress relaxation, G(t), and the damping function, h(γ), i.e. G(t, γ)=G(t) h(γ). G(t) is simply represented as a three-parameter exponential serial and h(γ) has a sigmoidal form with two parameters. The parameters are identified by adopting an efficient optimization method proposed by Stango et al. The comparison between the experimental results and the model-predicted values indicates that this mathematical model can accurately predict MR behavior.     

水工混凝土修补技术应用

针对水工混凝土的老化病害,介绍了不同类型修补材料的特点、性能、适用范围,以及修补技术应用中的一些实例和经验。     

石油化工生产火灾危险性分析

针对石油化工生产的特点,从物料特性、上艺装置、工艺控制参数、防火防爆安全装置、作业性质和消防安全设施等几方面综合分析其火灾危险性,并提出相应的防范措施,为消防安全评价提供依据。     

油气集输站场生活污水土地处理技术

通过对土地处理系统的介绍，结合油气站场污水的特点，分析了不同土地处理技术在实际中的设置情况和方式，给出一般的面积计算方法和结果，总结了土地处理的技术特点和应用前景。