基于双模型融合的大熊猫头部图像分割

在大熊猫(Ailuropoda melanoleuca)的迁地保护和种群饲养管理中,及时、快速地进行个体识别和行为监测,对其健康管理具有至关重要的作用。圈养大熊猫健康状况通常由专门的饲养人员肉眼观测,人力成本高、效率低并且缺乏时效性。基于图像的动物个体识别与行为分析技术效率高、时间成本低,已经成为新的监测发展趋势。已有研究提出,通过大熊猫面部图像的检测和分析,可实现个体识别和行为分类。但该方法依然存在检测精度不足导致识别准确率难以提升的问题。本文提出一种基于YOLOv3和Mask R-CNN的双模型融合方法,实现了大熊猫头部图像分割和精准检测。包含3个部分：YOLOv3完成头部检测,Mask R-CNN完成大熊猫轮廓分割,然后将两个模型的输出进行交并比融合。结果显示,头部检测准确率为82.6%,大熊猫轮廓分割准确率为95.2%,总体头部轮廓分割准确率为87.1%。该方法对大熊猫头部图像的识别率和分割准确率高,为大熊猫的个体识别、性别分类提供了帮助,为行为分析提供了技术参考。     

基于最大熵和改进PCNN的医学图像自动分割算法研究与实现

本文提出了基于最大熵和改进的PCNN(Pulse Coupled Neural Network)相结合的新方法,采用最大熵确定PCNN网络的循环迭代次数.提出的方法无需考虑PCNN参数的选择,可有效的自动分割各种医学图像,同时利用最大熵得到最优分割结果.该方法对于PCNN理论在医学图像分割领域的应用有着重要的意义.     

基于深度学习的阴道微生态病理图像自动诊断

阴道微生态病理图像是诊断细菌性阴道病的重要依据,但对其人工分析需要花费大量时间精力,导致诊断效率不高,因此需要寻求针对病理图像的自动诊断新方法.本文提出一种阴道微生态病理图像自动诊断模型ResLab,该模型以阴道微生态病理图像作为训练数据集,利用深度学习技术对病理图像进行端到端分析,预测Nugent评分,辅助医生进行分...     

基于目标检测的东北虎个体自动识别

东北虎个体的自动识别是种群数量评估和制定有效保护策略的重要基础。以东北虎林园和怪坡虎园38 只虎为研究对象,将目标检测方法首次应用到东北虎个体识别研究中,采用多种深度卷积神经网络模型,以实现虎个体的自动识别。首先通过相机在不同角度对 38 只东北虎进行拍摄取样,建立包含13579张图像的虎样本数据集。由于虎的体侧条纹信息不具有对称性,所以运用单次多盒目标检测（Single Shot MultiBox Detector, SSD）方法,对虎的躯干左侧条纹、右侧条纹以及脸部等不同部位图像,进行自动检测并分割提取,极大节省手工截取时间。在检测分割出的左右侧及脸部不同部位图片基础上,运用上、下、左、右平移变换进行数据增强,使图片数目扩大为原来的5 倍。采用LeNet、AlexNet、ZFNet、VGG16、ResNet34共5 种卷积神经网络模型进行个体自动识别。为了提高识别准确率,运用平均值和最大值不同组合方式来优化池化操作,并在全连接层引入概率分别为0.1、0.2、0.3、0.4的丢弃（Dropout）操作防止过拟合。实验表明,目标检测模型耗时较少,截取分割老虎不同部位条纹能达到0.6 s/张,远快于人工截取速度,并且在测试集上准确率能达到97.4%。不同姿态下的目标部位都能正确识别并分割。ResNet34模型的准确率优于其他网络模型,左右侧条纹以及脸部图像识别准确率分别为93.75%、97.01%和 86.28%,右侧条纹识别准确率优于左侧条纹和脸部图像。研究为野生虎自动相机影像的识别提供技术参考。在未来研究中,对东北虎个体影响数据进行扩充,选取更多影像数据进行训练,使网络具有更强的适应性,从而实现更准确的个体识别。     

Efficient liver segmentation in CT images based on graph cuts and bottleneck detection

Liver segmentation from abdominal computed tomography (CT) volumes is extremely important for computer-aided liver disease diagnosis and surgical planning of liver transplantation. Due to ambiguous edges, tissue adhesion, and variation in liver intensity and shape across patients, accurate liver segmentation is a challenging task. In this paper, we present an efficient semi-automatic method using intensity, local context, and spatial correlation of adjacent slices for the segmentation of healthy liver regions in CT volumes. An intensity model is combined with a principal component analysis (PCA) based appearance model to exclude complex background and highlight liver region. They are then integrated with location information from neighboring slices into graph cuts to segment the liver in each slice automatically. Finally, a boundary refinement method based on bottleneck detection is used to increase the segmentation accuracy. Our method does not require heavy training process or statistical model construction, and is capable of dealing with complicated shape and intensity variations. We apply the proposed method on XHCSU14 and SLIVER07 databases, and evaluate it by MICCAI criteria and Dice similarity coefficient. Experimental results show our method outperforms several existing methods on liver segmentation.     

Rotationally resliced 3D prostate segmentation of MR images using Bhattacharyya similarity and active band theory

PurposeIn this article, we propose a novel, semi-automatic segmentation method to process 3D MR images of the prostate using the Bhattacharyya coefficient and active band theory with the goal of providing technical support for computer-aided diagnosis and surgery of the prostate.MethodsOur method consecutively segments a stack of rotationally resectioned 2D slices of a prostate MR image by assessing the similarity of the shape and intensity distribution in neighboring slices. 2D segmentation is first performed on an initial slice by manually selecting several points on the prostate boundary, after which the segmentation results are propagated consecutively to neighboring slices. A framework of iterative graph cuts is used to optimize the energy function, which contains a global term for the Bhattacharyya coefficient with the help of an auxiliary function. Our method does not require previously segmented data for training or for building statistical models, and manual intervention can be applied flexibly and intuitively, indicating the potential utility of this method in the clinic.ResultsWe tested our method on 3D T2-weighted MR images from the ISBI dataset and PROMISE12 dataset of 129 patients, and the Dice similarity coefficients were 90.34 ± 2.21% and 89.32 ± 3.08%, respectively. The comparison was performed with several state-of-the-art methods, and the results demonstrate that the proposed method is robust and accurate, achieving similar or higher accuracy than other methods without requiring training.ConclusionThe proposed algorithm for segmenting 3D MR images of the prostate is accurate, robust, and readily applicable to a clinical environment for computer-aided surgery or diagnosis.     

基于多尺度分割和决策树算法的山区遥感影像变化检测方法——以四川攀西地区为例

山区遥感影像变化检测面临地形效应明显、空间异质性高等不利因素的影响,构建适用于复杂地形条件的变化检测方法一直是遥感应用研究的难点。在对影像进行多尺度分割的基础上,构建对象的多种光谱、形状及地形特征,将地形阴影、物候等造成的虚假变化当作"未变化"训练样本,利用决策树算法自动提取检测规则,建立复杂地形条件下面向对象的遥感影像变化检测方法,并将该方法用于四川攀西山区1989年和2009年TM影像的检测试验,最后对方法的不足和改进措施进行了讨论。主要结论包括:(1)文中构建的方法能够有效减弱山区复杂地形条件对遥感影像变化检测的不利影响,采用地面调查数据和分层随机采样的总体验证精度为93.57%,Kappa系数为0.8706。(2)C5.0决策树算法对于只有"变化"和"未变化"两种类别且同类间训练样本高度异质化的影像分类仍能取得较好的效果,具有较好的鲁棒性和适应能力。通过将地形、物候等引起的虚假变化当作"未变化"训练样本可以有效提高检测精度。(3)光谱特征仍是TM影像遥感分析的主要信息源,影像间NDVI的差值对于植被覆盖区域土地覆盖格局变化的检测具有良好的表征作用。(4)攀西地区1989—2009年间土地覆盖格局变化明显且与人类活动关系密切,典型的驱动方式包括退耕还林(草)工程、水利工程建设和矿山开采等。共检测出变化面积740.2km2,占影像总面积的2.49%。     

Automatic detection of fish and tracking of movement for ecology

1. Animal movement studies are conducted to monitor ecosystem health, understand ecological dynamics, and address management and conservation questions. In marine environments, traditional sampling and monitoring methods to measure animal movement are invasive, labor intensive, costly, and limited in the number of individuals that can be feasibly tracked. Automated detection and tracking of small‐scale movements of many animals through cameras are possible but are largely untested in field conditions, hampering applications to ecological questions.
2. Here, we aimed to test the ability of an automated object detection and object tracking pipeline to track small‐scale movement of many individuals in videos. We applied the pipeline to track fish movement in the field and characterize movement behavior. We automated the detection of a common fisheries species (yellowfin bream, Acanthopagrus australis) along a known movement passageway from underwater videos. We then tracked fish movement with three types of tracking algorithms (MOSSE, Seq‐NMS, and SiamMask) and evaluated their accuracy at characterizing movement.
3. We successfully detected yellowfin bream in a multispecies assemblage (F1 score =91%). At least 120 of the 169 individual bream present in videos were correctly identified and tracked. The accuracies among the three tracking architectures varied, with MOSSE and SiamMask achieving an accuracy of 78% and Seq‐NMS 84%.
4. By employing this integrated object detection and tracking pipeline, we demonstrated a noninvasive and reliable approach to studying fish behavior by tracking their movement under field conditions. These cost‐effective technologies provide a means for future studies to scale‐up the analysis of movement across many visual monitoring systems.

     

基于邻域最大差值与区域合并的油茶毒蛾幼虫图像分割

【目的】油茶树害虫的种类较多,其中油茶毒蛾Euproctis pseudoconspersa幼虫是危害较大的害虫之一。为完成油茶毒蛾幼虫的自动检测需要对其图像进行分割,油茶毒蛾幼虫图像的分割效果直接影响到图像的自动识别。【方法】本文提出了基于邻域最大差值与区域合并的油茶毒蛾幼虫图像分割算法,该方法主要是对相邻像素RGB的3个分量进行差值运算,最大差值若为0,则进行相邻像素合并得出初始的分割图像,根据合并准则进一步合并,得到最终分割结果。【结果】实验结果表明,该算法可以快速有效地将油茶毒蛾幼虫图像中的背景和虫体分割开来。【结论】使用JSEG分割算法、K均值聚类分割算法、快速几何可变形分割算法和本文算法对油茶毒蛾幼虫图像进行分割,将结果进行对比发现本文方法的分割效果最佳,且处理时间较短。     

A highly selective and sensitive turn‐on fluorescent probe for the detection of Al3+ and its bioimaging

A novel fluorescent sensor, 1‐((2‐hydroxynaphthalen‐1‐yl)methylene)urea (ocn) has been designed and applied as a highly selective and sensitive fluorescent probe for recognition of Al³⁺ in Tris–HCl (pH = 7.20) solution. The probe ocn exhibits an excellent selectivity to Al³⁺ over other examined metal ions, anions and amino acids with a prominent fluorescence ‘turn‐on’ at 438 nm. ocn binds to Al³⁺ with a 2:1 binding stoichiometry and the detection limit was 0.3 μM. Furthermore, its capability of biological application was evaluated and the results showed that the sensor could be used to detect Al³⁺ in living cells.     

Upregulation of endogenous glutathione system by 3H-1,2-dithiole-3-thione in pancreatic RINm5F beta-cells as a novel strategy for protecting against oxidative beta-cell injury

This study was undertaken to investigate the inducibility of glutathione (GSH), glutathione reductase (GR) and glutathione peroxidase (GPx) by 3H-1,2-dithiole-3-thione (D3T) in beta-cells, and the resultant cytoprotection against oxidant injury. Incubation of the insulin-secreting RINm5F cells with D3T led to significant induction of GSH, GR and GPx. D3T-mediated induction of GSH was abolished by buthionine sulfoximine (BSO), suggesting a critical involvement of γ-glutamylcysteine ligase (γGCL). Consistently, incubation of RINm5F cells with D3T resulted in increased expression of γGCL protein and mRNA. Pretreatment of RINm5F cells with D3T provided remarkable protection against oxidant-elicited cytotoxicity. On the other hand, depletion of cellular GSH by BSO sensitized RINm5F cells to oxidant injury. Furthermore, cotreatment of RINm5F cells with BSO to reverse D3T-mediated GSH induction abolished the cytoprotective effects of D3T on oxidant injury. Taken together, this study demonstrates that upregulation of glutathione system by D3T is effective for protecting against oxidative beta-cell injury.     

Application of liquid chromatography-tandem mass spectrometry method for the analysis of new nonselective beta-adrenergic blocker 1-(1-H-indol-4-yloxy)-3-{[2-(2-methoxy phenoxy)ethylo]amino}propan-2-ol (2F109) in rat plasma

A sensitive and specific liquid chromatography electrospray ionization-tandem mass spectrometry method for the enantioselective determination of the novel beta-adrenolytic compound, 1-(1-H-indol-4-yloxy)-3-{[2-(2-methoxyphenoxy)ethylo]amino} propan-2-ol, in rat plasma has been developed and validated. Chromatography was performed on a reversed-phase Chiralcel OD-RH analytical column (150x4.6 mm, 5 microm, Daicel Chemical Industries, Tokyo, Japan) with isocratic elution using a mobile phase containing acetonitrile and water with 0.01% formic acid. Detection was achieved by an Applied Biosystems MDS Sciex (Concord, Ontario, Canada) API 2000 triple quadrupole mass spectrometer. Electrospray ionization (ESI) was used for ion production. The limit of detection in the MRM mode was found to be 1.25 ng/ml. The limit of quantification of both enantiomers was 2.5 ng/ml. The precision and accuracy for both intra- and inter-day determination of 2F109 enantiomers ranged from 2.6 to 12% and from 89.1 to 107.1%. This analytical method allowed us to carry out pharmacokinetic studies in rats. Our findings demonstrate that 2F109 shows stereoselective disposition in rat plasma after i.v. administration. The terminal half-lives of (+)-(R)-2F109 and (-)-(S)-2F109 were 33.5 and 42.6 min, respectively. The AUC0-inf of (+)-(R)-2F109 exceeded that of (-)-(S)-2F109.