专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明申请

WO2014144103A1 CHARACTERIZING PATHOLOGY IMAGES WITH STATISTICAL ANALYSIS OF LOCAL NEURAL NETWORK RESPONSES 审中-公开
标题翻译：通过局部神经网络响应的统计分析来表征病理学图像
公开(公告)号：WO2014144103A1
公开(公告)日：2014-09-18
申请号：PCT/US2014/028375
申请日：2014-03-14
申请人： SONY CORPORATION , XU, Xun , NAKAMURA, Akira , WANG, Su
发明人： XU, Xun , NAKAMURA, Akira , WANG, Su
IPC分类号： G06K9/00
CPC分类号： G06K9/00147 , G06K9/6273
摘要： For digital pathology imaging, intelligent processing, such as automatic recognition or content-based retrieval, is one significant benefit that drives the wide application of this technology. Before any intelligent processing on pathology images, every image is converted into a feature vector which quantitatively capture its visual characteristics. An algorithm characterizing pathology images with statistical analysis of local responses of neural networks is described herein. The algorithm framework enables extracting sophisticated textural features that are well adapted to the image data of interest.
摘要翻译：对于数字病理成像，诸如自动识别或基于内容检索的智能处理是推动该技术的广泛应用的一个重要益处。在对病理图像进行任何智能处理之前，将每个图像转换为定量捕获其视觉特征的特征向量。本文描述了利用神经网络的局部响应的统计分析来表征病理图像的算法。该算法框架能够提取出适合于感兴趣的图像数据的复杂纹理特征。

2. 发明申请

WO2018067234A1 AUTOMATED NUCLEI AREA/NUMBER ESTIMATION FOR IHC IMAGE ANALYSIS 审中-公开
标题翻译： IHC图像分析的自动核面积/数量估计
公开(公告)号：WO2018067234A1
公开(公告)日：2018-04-12
申请号：PCT/US2017/047004
申请日：2017-08-15
申请人： SONY CORPORATION , WANG, Su
发明人： WANG, Su , XU, Xun , NAKAMURA, Akira
IPC分类号： G06T7/00 , G06T7/11 , G06T7/136 , G06K9/00
摘要： Automated nuclei area/number estimation utilizes a two-stage estimation framework - area estimation first followed by number estimation. After determining area information, each local patch's shape features are able to be extracted to define a local voting rule. The resulting voting score determines the strength of each local voting peak. The number of voting peaks is exactly the number of nuclei.
摘要翻译：自动化核区域/数量估计利用两阶段估计框架 - 首先进行区域估计，然后进行数量估计。确定区域信息后，可以提取每个本地补丁的形状特征以定义本地投票规则。由此产生的投票分数决定了每个地方投票高峰的强度。投票峰的数量正好是核的数量。

3. 发明申请

WO2013142107A1 GRAPH CUTS-BASED INTERACTIVE SEGMENTATION OF TEETH IN 3-D CT VOLUMETRIC DATA 审中-公开
标题翻译： 3-D CT体积数据中基于图形图的交互式分类
公开(公告)号：WO2013142107A1
公开(公告)日：2013-09-26
申请号：PCT/US2013/030090
申请日：2013-03-10
申请人： SONY CORPORATION , WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira
发明人： WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira
IPC分类号： G06K9/00
CPC分类号： G06T7/162 , G06T7/11 , G06T7/194 , G06T2207/10081 , G06T2207/20041 , G06T2207/20096 , G06T2207/30036
摘要： An interactive segmentation framework for 3-D teeth CT volumetric data enables a user to segment an entire dental region or individual teeth depending upon the types of user input. Graph cuts-based interactive segmentation utilizes a user's scribbles which are collected on several 2-D representative CT slices and are expanded on those slices. Then, a 3-D distance transform is applied to the entire CT volume based on the expanded scribbles. Bony tissue enhancement is added before feeding 3-D CT raw image data into the graph cuts pipeline. The segmented teeth area is able to be directly utilized to reconstruct a 3-D virtual teeth model.
摘要翻译：用于3D牙齿CT体积数据的交互式分割框架使用户能够根据用户输入的类型来分割整个牙齿区域或单个牙齿。基于图切割的交互式分割利用用户的涂鸦，这些涂鸦被收集在几个二维代表性的CT切片上，并在这些切片上展开。然后，基于扩展的涂鸦将3-D距离变换应用于整个CT体积。在将3-D CT原始图像数据提供给图形切割管道之前，添加骨组织增强。分段牙齿区域能够直接用于重建3-D虚拟牙齿模型。

4. 发明申请

WO2019012365A1 A FAST, PROGRESSIVE APPROACH TO SUPERVOXEL-BASED SPATIAL TEMPORAL VIDEO SEGMENTATION 审中-公开
公开(公告)号：WO2019012365A1
公开(公告)日：2019-01-17
申请号：PCT/IB2018/054834
申请日：2018-06-29
申请人： SONY CORPORATION
发明人： XU, Xun , NAKAMURA, Akira
IPC分类号： G06T7/11 , G06T7/162
摘要： The two-step architecture of the supervoxel-based spatial temporal video segmentation method ensures speed and scalability. The computationally intensive first step uses a highly efficient super-voxel segmentation method. The second step is done over pre-grouped super- voxels, hence has much lower temporal and spatial complexity. The progressive segmentation scheme deployed in the first step enables segmenting huge input volume part by part, without loading all the data into the memory which may be infeasible. At the same time, the progressive segmentation is able to effectively prevent seam artifacts, leading to segmentation results virtually identical to those of whole volume processing.

5. 发明申请

WO2012148619A1 SUPERPIXEL SEGMENTATION METHODS AND SYSTEMS 审中-公开
标题翻译： SUPERPIXEL分类方法和系统
公开(公告)号：WO2012148619A1
公开(公告)日：2012-11-01
申请号：PCT/US2012/031001
申请日：2012-03-28
申请人： SONY CORPORATION , LV, Xutao , WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira
发明人： LV, Xutao , WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira
IPC分类号： G06T9/20
CPC分类号： G06T3/4053
摘要： Systems and methods for implementing a superpixel image segmentation technique using a boundary preserving distance metric are disclosed. The disclosed technique segments a digital image into superpixels comprising contiguous pixel regions sharing similar characteristics. Superpixel image segmentation techniques presented herein utilize a boundary preserving distance metric. A boundary preserving distance metric presented herein measures the similarity between two pixels of a digital image at least partially based on a boundary probability values of the two pixels and surrounding pixels.
摘要翻译：公开了使用边界保留距离度量来实现超像素图像分割技术的系统和方法。所公开的技术将数字图像分割成包含具有相似特征的相邻像素区域的超像素。本文提出的超像素图像分割技术利用边界保留距离度量。这里给出的边界保持距离度量至少部分地基于两个像素和周围像素的边界概率值来测量数字图像的两个像素之间的相似度。

6. 发明申请

WO2019012363A1 VISUAL QUALITY PRESERVING QUANTIZATION PARAMETER PREDICTION WITH DEEP NEURAL NETWORK 审中-公开
公开(公告)号：WO2019012363A1
公开(公告)日：2019-01-17
申请号：PCT/IB2018/054832
申请日：2018-06-29
申请人： SONY CORPORATION
发明人： XU, Xun , NAKAMURA, Akira
IPC分类号： H04N19/124 , H04N19/196 , H04N19/176 , H04N19/136 , G06N3/04 , G06N3/08
摘要： A QP mapping method is capable of preserving consistent visual quality across the encoded frame. It automatically assigns more bits to image blocks which are more sensitive to compression distortion. The texture-descriptive features employed for QP prediction are fast to compute and, together with a deep neural network, are able to effectively approximate the underlying QP mapping strategy deduced from a visual quality measure.

7. 发明申请

WO2014144396A1 MANIFOLD-AWARE RANKING KERNEL FOR INFORMATION RETRIEVAL 审中-公开
标题翻译： MANIFOLD-AWARE排名信息查询
公开(公告)号：WO2014144396A1
公开(公告)日：2014-09-18
申请号：PCT/US2014/028787
申请日：2014-03-14
申请人： SONY CORPORATION , XU, Xun , NAKAMURA, Akira , GONG, Dian , WANG, Su
发明人： XU, Xun , NAKAMURA, Akira , GONG, Dian , WANG, Su
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A manifold-aware ranking kernel (MARK) for information retrieval is described herein. The MARK is implemented by using supervised and unsupervised learning. MARK is ranking-oriented such that the relative comparison formulation directly targets on the ranking problem, making the approach optimal for information retrieval. MARK is also manifold-aware such that the algorithm is able to exploit information from ample unlabeled data, which helps to improve generalization performance, particularly when there are limited number of labeled constraints. MARK is nonlinear: as a kernel-based approach, the algorithm is able to lead to a highly non-linear metric which is able to model complicated data distribution.
摘要翻译：本文描述了用于信息检索的歧管感知排名内核（MARK）。 MARK通过使用监督和无监督的学习来实现。 MARK以排名为导向，相对比较方式直接针对排名问题，使得该方法对于信息检索最为理想。 MARK也是歧管感知的，使得算法能够利用来自充足的未标记数据的信息，这有助于提高泛化性能，特别是当有限数量的标记约束时。 MARK是非线性的：作为基于内核的方法，该算法能够导致高度非线性的度量，能够对复杂的数据分布进行建模。

8. 发明申请

WO2014144234A1 COMBINING INFORMATION OF DIFFERENT LEVELS FOR CONTENT-BASED RETRIEVAL OF DIGITAL PATHOLOGY IMAGES 审中-公开
标题翻译：用于基于内容的数字病理学图像检索的不同级别的组合信息
公开(公告)号：WO2014144234A1
公开(公告)日：2014-09-18
申请号：PCT/US2014/028551
申请日：2014-03-14
申请人： SONY CORPORATION , XU, Xun , DAI, Shengyang , NAKAMURA, Akira , WANG, Su
发明人： XU, Xun , DAI, Shengyang , NAKAMURA, Akira , WANG, Su
IPC分类号： A61B5/00
CPC分类号： G06F17/30247 , G06K9/4652 , G06K9/4671
摘要： Content-based retrieval of digital pathology images (DPI) is a fundamental component in an intelligent DPI processing and management system. One key issue of content-based DPI retrieval is how to represent an image as a feature vector, capturing its key information that is most relevant to the goal of retrieval. A unified framework of extracting information of different levels for DPI, namely low level color information, middle level texture information and high level diagnostic information is described herein. Such information from all the levels are integrated to the end of content-based DPI retrieval.
摘要翻译：数字病理图像（DPI）的基于内容的检索是智能DPI处理和管理系统的基础组件。基于内容的DPI检索的一个关键问题是如何将图像表示为特征向量，捕获与检索目标最相关的关键信息。本文描述了提取DPI不同级别信息的统一框架，即低级颜色信息，中级纹理信息和高级别诊断信息。来自所有级别的这些信息被集成到基于内容的DPI检索的结尾。

9. 发明申请

WO2013142109A1 FLUORESCENT DOT COUNTING IN DIGITAL PATHOLOGY IMAGES 审中-公开
标题翻译：数字病理图像中的荧光计数
公开(公告)号：WO2013142109A1
公开(公告)日：2013-09-26
申请号：PCT/US2013/030092
申请日：2013-03-10
申请人： SONY CORPORATION , WANG, Su , XU, Xun , NAKAMURA, Akira
发明人： WANG, Su , XU, Xun , NAKAMURA, Akira
IPC分类号： G06K9/46
CPC分类号： G06K9/0014 , G06K9/00147
摘要： Fluorescence in situ hybridization (FISH) enables the detection of specific DNA sequences in cell chromosomes by the use of selective staining. Due to the high sensitivity, FISH allows the use of multiple colors to detect multiple targets simultaneously. The target signals are represented as colored dots, and enumeration of these signals is called dot counting. Using a two-stage segmentation framework guarantees locating all potential dots including overlapped dots.
摘要翻译：荧光原位杂交（FISH）能够通过选择性染色检测细胞染色体中的特定DNA序列。由于高灵敏度，FISH允许使用多种颜色同时检测多个目标。目标信号表示为彩色点，这些信号的枚举称为点计数。使用两阶段分割框架可确保定位所有可能的点，包括重叠点。

10. 发明申请

WO2013142108A8 INTEGRATED INTERACTIVE SEGMENTATION WITH SPATIAL CONSTRAINT FOR DIGITAL IMAGE ANALYSIS 审中-公开
公开(公告)号：WO2013142108A8
公开(公告)日：2013-09-26
申请号：PCT/US2013/030091
申请日：2013-03-10
申请人： SONY CORPORATION , WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira , OHASHI, Takeshi , YOKONO, Jun
发明人： WANG, Su , DAI, Shengyang , XU, Xun , NAKAMURA, Akira , OHASHI, Takeshi , YOKONO, Jun
IPC分类号： G06K5/00
摘要： An integrated interactive segmentation with spatial constraint method utilizes a combination of several of the most popular online learning algorithms into one and implements a spatial constraint which defines a valid mask local to the user's given marks. Additionally, both supervised learning and statistical analysis are integrated, which are able to compensate each other. Once prediction and activation are obtained, pixel-wised multiplication is conducted to fully indicate how likely each pixel belongs to the foreground or background.

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式