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    • 3. 发明授权
    • Medical image processing methodology for detection and discrimination of objects in tissue
    • 用于组织中物体检测和辨别的医学图像处理方法
    • US07899514B1
    • 2011-03-01
    • US11340375
    • 2006-01-26
    • James H. KirklandKevin D. Nash
    • James H. KirklandKevin D. Nash
    • A61B5/05
    • G06T7/0012G06T2207/10088G06T2207/10116G06T2207/10132G06T2207/20132G06T2207/30068
    • A method and system for detecting and classifying anomalies in a medical image. During anomaly detection, once the intensity of an image pixel crosses a detection threshold, the pixel is detected and linking inputs are provided to its nearest-neighbor pixels. The linking inputs increase the intensities of the neighbor pixels, which may result in the detection of these nearest-neighbor pixels if their linked intensities are above the threshold. Each detected anomaly is classified by determining a genetic response surface methodology (GRSM) model for the detected anomaly, determining a cancerous GRSM model from a database of cancerous anomalies, and comparing the cancerous GRSM model to the GRSM model for the detected anomaly to classify the detected anomaly as cancerous or non-cancerous.
    • 一种用于检测和分类医学图像中的异常的方法和系统。 在异常检测期间,一旦图像像素的强度超过检测阈值,则检测像素,并将链接输入提供给其最近邻像素。 链接输入增加相邻像素的强度,如果它们的链接强度高于阈值,则可能导致这些最近邻像素的检测。 通过确定检测到的异常的遗传反应表面方法(GRSM)模型,从癌症异常数据库确定癌性GRSM模型,并将癌GRSM模型与GRSM模型进行比较,对检测到的异常进行分类,对所检测到的异常进行分类,对 检测到异常为癌性或非癌性。