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。     

基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

HEGF中CO井筒流动及扩散规律研究

目前,高能气体压裂广泛的应用于低渗透油气田,可以有效清除近井地带由于钻井、射孔和各种措施造成的污染和堵塞,达到油气井增产、注水井增注的目的。但最近一些低渗透油气田却出现了频繁的CO气体中毒事件,给油田及员工带来巨大的损失。针对这一现象,运用现场数据以及物理模拟和数学模拟方法首次通过对CO气体流动、扩散等的综合研究,建立了CO井筒流动及大气扩散模型。同时,也考察了井筒压力、气油比、风速、气体泄放速率、大气稳定度等主要因素对CO气体扩散的影响。通过现场实例计算,证实模型具有较高的准确性。此项工作的完成为建立监控系统提供基础技术依据,同时对合理、有效的开发油气田以及煤层气的开发将具有重要的实际意义。     

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.     

半导体传感器在生物分析科学中的应用(英文)

回顾了半导体生化传感器 (ISFET 和 LA PS)在医学监测、免疫检测、免疫分析、D N A 杂交以及细胞培养等方面应用的进展。为使半导体器件适用于生化检测,对其中所采用的检测手段和取得的研究结果进行了分析。展望了通过与微流体网络相结合,基于半导体传感器的实验室芯片化的可行性。     

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。     

纳米AlN粉末的制备与烧结

利用低温燃烧合成前驱物制备出平均粒度为100 nm的AlN陶瓷粉末,比较了该粉末的常压烧结和放电等离子烧结的特性.实验表明:以合成的AlN粉末为原料,添加5%(质量比)Y2O3作为烧结助剂,在常压、流动N2气氛下1600℃保温3 h,制备出平均晶粒尺寸为4～8 μm、密度为3.28 g·cm-3的AlN陶瓷;将同样的粉末不加任何烧结助剂,采用SPS技术在1600℃保温4 min,得到密度为3.26 g·cm-3的AlN陶瓷,晶粒度约为1～2μm.     

复杂土坝的渗流安全分析评价

根据福华山土坝的渗流观测资料,建立了测压管水位的回归统计模型,定量分析了各影响量(水位分量、时效分量)对测压管水位的影响效应。在此基础上,结合观测资料,采用有限元法反演了大坝各填筑区的渗透系数,并综合评价了大坝的渗流性态。