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.

     

In-situ crystal growth and photoluminescence properties of YBO3: Tb3+ microstructures

Three-dimensional (3D) YBO₃:Tb³⁺ flower-like and dense flower-like hierarchitecture constituted of nanoflakes are solvothermally synthesized in the presence of polyborate precursors in the mixture of ethanol and water. The growth process of the YBO₃:Tb³⁺ flowers and dense flowers was explored based on the time-dependent experiment and the results showed that the growth mechanism follows an in situ growth rather than self-assembly process as reported previously. YBO₃:Tb³⁺ morphologies composed of nanoflakes are achieved by controlling the concentration of ethanol and dependence of photoluminescence on morphology was studied. Remarkable photoluminescence enhancement was observed for YBO₃:Tb³⁺ with flower-like morphology demonstrating the potential of the microstructure in future applications as a green phosphor. Such a synthetic method and growth mechanism may be applied to fabricate complex 3D architectures of other materials.     

土壤中石油污染物的脱附过程

文章中主要采用有机溶剂萃取法（OSE）对高浓度石油污染土壤进行修复，经过精馏操作，有效回收原油，建立脱附等温曲线，研究了石油污染物在土壤-有机溶剂两相间的迁移规律。     

变频器调速装置节能浅析

1概述 近十多年来,随着电力电子技术、微电子技术及现代控制理论的发展,变频调速技术已经广泛地用于交流电动机的速度控制,其最主要的特点是具有高效率的驱动性能及良好的控制特性.它是一种高新技术电力节能装置,它通过改变（降低）电源工作频率,来降低动力设备（电机）的转速,减少设备的输出功率,达到输出功率与工作负荷的最佳匹配,实现节能目的,有效地提高了经济效益和产品质量.几乎可以说,有电动机的地方就有变频器,在一切需要进行速度控制的场合,变频器以其操作方便、体积小、控制性能高而获得广泛应用.     

简化形式的系统EMC预测分析技术概述

本文探讨了系统级简化形式的电磁兼容性预测分析方法，该方法对于只有几对发-收干扰对的系统EMI的预测分析简洁有效，它避免了大系统间繁复的建模与大量的数据采集及其计算工作，从而对于只考虑其结果的系统间的EMC预测分析提高了效率。     

动态规划原理在骨料用料方案设计中的应用

在砂石料场规划中常面临多供料点、多需料点条件下的用料方案设计问题。本文应用动态规划原理,提出了“多供点—多需点”物料调配优化计算方法及框图,编制了相应的计算程序。工程实例分析表明,该方法在骨料综合成本和弃料量等方面均优于常规方法,具有一定的应用价值。     

渤海湾盆地石油地质储量和产量增长趋势的预测

渤海湾盆地的石油地质储量发现过程具有明显的渐进性、阶段性和长期性，石油产量的增长也具有一定的起伏性，用一个周期的单旋回哈伯特模型难以预测其发展趋势。通过分析渤海湾盆地的勘探开发历程，结合新一轮常规油气资源评价的结果，分别采用4个和3个哈伯特旋回拟合石油地质储量发现和产量增长曲线。预测结果显示，2005-2015年渤海湾盆地处于石油地质储量发现高峰期，2015年左右其石油产量达到高峰，之后处于下降趋势。实践证明，利用多旋回哈伯特模型对具有“多峰”特征的石油地质储量和产量的未来趋势进行预测是一种有效的方法。     

关于以能力建设为基础的培训工作研究

提高对人才能力建设的培训水平,是国有企业培训机构在人才培训工作与人力资源开发过程中需要深入研究、探索的重要课题。针对中国石油化工集团公司推进改革发展、实现企业战略目标对高级管理人才的需求,以企业高级管理人才任职前培训为目标,在培训需求研究、课程设计与内容开发、教学手段和方法、培训过程管理与质量保证机制、培训效果评估等方面进行研究。