公开(公告)号：US5984870A

公开(公告)日：1999-11-16

申请号：US900192

申请日：1997-07-25

申请人： Maryellen L. Giger ,  Hania Al-Hallaq ,  Dulcy Wolverton ,  Ulrich Bick

发明人： Maryellen L. Giger ,  Hania Al-Hallaq ,  Dulcy Wolverton ,  Ulrich Bick

IPC分类号： A61B20060101 ,  A61B8/00 ,  G06T7/00

CPC分类号： G06T7/0012 ,  G06T2207/30068

摘要： A method and apparatus for the computerized automatic analysis of lesions in ultrasound images, including the computerized analysis of lesions in the breast, using gradient, gray-level, and texture based measures. Echogenicity features are developed to assess the characteristics of the lesions and in some cases give an estimate of the likelihood of malignancy or of prognosis. The output from the computerized analysis is used in making a diagnosis and/or prognosis. For example, with the analysis of the ultrasound images of the breast, the features can be used to either distinguish between malignant and benign lesions, or distinguish between (i.e., diagnosis) the types of benign lesions such as benign solid lesions (e.g., fibroadenoma), simple cysts, complex cysts, and benign cysts. The ultrasound image features can be merged with those from mammographic and/or magnetic resonance images of the same lesion for classification by means of a common artificial neural network.

摘要翻译： 一种用于计算机化自动分析超声图像中病变的方法和装置，包括使用梯度，灰度和基于纹理的手段对乳房病变进行计算机化分析。 开发Echogenicity特征来评估病变的特征，并且在某些情况下给出恶性肿瘤或预后的可能性的估计。 计算机分析的输出用于诊断和/或预后。 例如，通过对乳房超声图像的分析，这些特征可以用于区分恶性和良性病变，或区分（即，诊断）良性病变的类型，例如良性固体病变（例如，纤维腺瘤 ），简单囊肿，复杂囊肿和良性囊肿。 超声图像特征可以与来自同一病变的乳房X线照相和/或磁共振图像的那些融合，以便通过普通人造神经网络分类。