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CHARACTERIZING LUNG NODULE RISK WITH QUANTITATIVE NODULE AND PERINODULAR RADIOMICS
专利权人:
发明人:
Anant Madabhushi,Mahdi Orooji,Mirabela Rusu,Philip Linden,Robert Gilkeson,Nathaniel Mason Braman,Mehdi Alilou
申请号:
US16043498
公开号:
US20180353149A1
申请日:
2018.07.24
申请国别(地区):
US
年份:
2018
代理人:
摘要:
Embodiments associated with classifying a region of tissue using features extracted from nodules and surrounding structures. One example apparatus includes a feature extraction circuit configured to automatically extract a first set of quantitative features from a nodule represented in at least one CT image, and automatically extract a second set of quantitative features from the lung parenchyma region immediately surrounding the nodule represented in the at least one CT image a feature selection circuit configured to select an optimally predictive feature set from the first set of quantitative features and the second set of quantitative features and a training circuit configured to train a classifier using the optimally predictive feature set to assign malignancy risk to a lung nodule represented in a CT image of a region of tissue demonstrating lung nodules. A prognosis or treatment plan may be provided based on the malignancy risk.
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中国工程科技知识中心
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