Method for constructing lung adenocarcinoma infiltration imaging omics classification model

The invention discloses a method for constructing lung adenocarcinoma infiltration imaging omics classification model, which comprises the following steps: by taking multiple groups of chest CT imagesunder different resolutions as objects, automatically detecting and segmenting pulmonary nodule lesi...

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Main Authors ZHOU ZHEN, YU HONG, ZHENG ZHICHUN, YIN LEKANG, CHEN YINAN, SHI DEJUN, TAO GUANGYU, YE XIAODAN, SHI JUEQIAN, ZHANG XIAOJUN, YU LINGMING
Format Patent
LanguageChinese
English
Published 26.03.2021
Subjects
CALCULATING
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Summary:The invention discloses a method for constructing lung adenocarcinoma infiltration imaging omics classification model, which comprises the following steps: by taking multiple groups of chest CT imagesunder different resolutions as objects, automatically detecting and segmenting pulmonary nodule lesions in the chest CT images through a chest CT pulmonary nodule detection and segmentation system, and obtaining a cytology type of each pulmonary nodule according to a pathological biopsy result, and obtaining a real label of wettability classification; using an open-source Pyraliomics software library to automatically extract a required extraction number of image omics features set for each pulmonary nodule lesion in the segmentation result, and forming a training data set in combination withthe wettability real label of each pulmonary nodule; aiming at the CT images with each resolution, respectively training a set of wettability classification prediction model by taking pulmonary noduleimage omics characteristic
Bibliography:Application Number: CN202011442095