公开(公告)号：US5857030A

公开(公告)日：1999-01-05

申请号：US629694

申请日：1996-04-09

申请人： Roger Stephen Gaborski ,  Yuan-Ming Fleming Lure ,  Thaddeus Francis Pawlicki

发明人： Roger Stephen Gaborski ,  Yuan-Ming Fleming Lure ,  Thaddeus Francis Pawlicki

IPC分类号： G06K9/62 ,  G06T5/00 ,  G06T7/00 ,  G06K9/80

CPC分类号： G06K9/62 ,  G06T7/0012 ,  G06T7/0081 ,  G06T7/0091 ,  G06T2207/10116 ,  G06T2207/20084 ,  G06T2207/30068 ,  G06T2207/30096

摘要： An automated method and system for digital imaging processing of radiologic images, wherein digital image data is acquired and subjected to multiple phases of digital imaging processing. During the Pre-Processing stage, simultaneous box-rim filtering and k-nearest neighbor processing and subsequent global thresholding are performed on the image data to enhance object-to-background contrast, merge subclusters and determine gray scale thresholds for further processing. Next, during the Preliminary Selection phase, body part segmentation, morphological erosion processing, connected component analysis and image block segmentation occurs to subtract unwanted image data preliminarily identify potentials areas including abnormalities. During the Pattern Classification phase, feature patterns are developed for each area of interest, a supervised, back propagation neural network is trained, a feed forward neural network is developed and employed to detect true and several false positive categories, and two types of pruned neural networks are utilized in connection with a heuristic decision tree to finally determine whether the regions of interest are abnormalities or false positives.

摘要翻译： 一种用于放射图像的数字成像处理的自动化方法和系统，其中获取数字图像数据并进行数字成像处理的多个阶段。 在预处理阶段期间，对图像数据执行同时的盒边缘滤波和k个最近邻处理以及随后的全局阈值处理，以增强对象对背景对比度，合并子集群并确定用于进一步处理的灰度阈值。 接下来，在初步选择阶段，进行身体部位分割，形态侵蚀处理，连通分量分析和图像块分割，以减去不需要的图像数据，初步识别包括异常的电位区域。 在模式分类阶段，针对感兴趣的每个区域开发特征模式，对受监督的反向传播神经网络进行了训练，开发了一种前馈神经网络，用于检测真假和正误分类，以及两种类型的修剪神经 网络利用启发式决策树来最终确定感兴趣的区域是异常还是误报。

公开(公告)号：US5528703A

公开(公告)日：1996-06-18

申请号：US179812

申请日：1994-01-10

申请人： Shih-Jong J. Lee

发明人： Shih-Jong J. Lee

IPC分类号： G06T1/00 ,  G01N15/14 ,  G06K9/00 ,  G06K9/32 ,  G06K9/74 ,  G06T5/00 ,  G06T7/00 ,  G06T7/60 ,  G06K9/42

CPC分类号： G06T5/40 ,  G01N15/1475 ,  G06K9/00127 ,  G06K9/32 ,  G06T5/009 ,  G06T7/0012 ,  G06T7/004 ,  G06T7/0081 ,  G06T7/0083 ,  G06T7/0091 ,  G06T2207/10056 ,  G06T2207/20144 ,  G06T2207/20224 ,  G06T2207/30024

摘要： The present invention provides a method for identifying the size, shape, and location of objects in a specimen wherein the image of the specimen is represented by image data and wherein the image data is processed to provide mask data representing a mask wherein the mask identifies the size, shape, and location of the object. Generally, the method includes the step of enhancing the image and creating a threshold image wherein the threshold image includes a threshold intensity value associated with each pixel of the image. The threshold image is combined with the original image to provide a mask image that identifies the size, shape, and location of the objects. The mask image may be further refined to ensure accurate identification of the object. Various other techniques are disclosed within the general method for processing image data.

摘要翻译： 本发明提供一种用于识别样本中的物体的尺寸，形状和位置的方法，其中样本的图像由图像数据表示，并且其中处理图像数据以提供表示掩模的掩模数据，其中掩模识别 大小，形状和位置。 通常，该方法包括增强图像和创建阈值图像的步骤，其中阈值图像包括与图像的每个像素相关联的阈值强度值。 阈值图像与原始图像组合以提供识别对象的大小，形状和位置的掩模图像。 可以进一步改进掩模图像以确保对象的准确识别。 在用于处理图像数据的一般方法中公开了各种其它技术。