Invention Grant
US08208697B2 Method and apparatus for automatically developing a high performance classifier for producing medically meaningful descriptors in medical diagnosis imaging
有权
用于自动开发用于在医学诊断成像中产生医学上有意义的描述符的高性能分类器的方法和装置
- Patent Title: Method and apparatus for automatically developing a high performance classifier for producing medically meaningful descriptors in medical diagnosis imaging
- Patent Title (中): 用于自动开发用于在医学诊断成像中产生医学上有意义的描述符的高性能分类器的方法和装置
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Application No.: US11721999Application Date: 2005-12-13
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Publication No.: US08208697B2Publication Date: 2012-06-26
- Inventor: James David Schaffer , Walid Ali , Larry J. Eshelman , Claude Cohen-Bacrie , Jean-Michel Lagrange , Claire Levrier , Nicholas Villain , Robert R. Entrekin
- Applicant: James David Schaffer , Walid Ali , Larry J. Eshelman , Claude Cohen-Bacrie , Jean-Michel Lagrange , Claire Levrier , Nicholas Villain , Robert R. Entrekin
- Applicant Address: NL Eindhoven
- Assignee: Koninklijke Philips Electronics N.V.
- Current Assignee: Koninklijke Philips Electronics N.V.
- Current Assignee Address: NL Eindhoven
- International Application: PCT/IB2005/054220 WO 20051213
- International Announcement: WO2006/064470 WO 20060622
- Main IPC: G06K9/36
- IPC: G06K9/36

Abstract:
A method for determining the presence or absence of malignant features in medical images, wherein a plurality of base comparison or training images of various types of lesions taken of actual patient is examined by one or more image reading experts to create a first database array. Low-level features of each of the lesions in the same plurality of base comparisons or training images are determined using one or more image processing algorithms to obtain a second database array set. The first and second database array set are combined to create a training database array set which is input to a learning system that discovers/learns a classifier that maps from a subset of the low-level features to the expert's evaluation in the first database array set. The classifier is used to determine the presence of a particular mid-level feature in an image of lesion in a patient based solely on the image.
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