Multi-modal parameter model optimization fusion method based on image omics features

Abstract

The invention discloses a multi-modal parameter model optimization fusion method based on image omics features. The method comprises the following steps: obtaining medical images of a plurality of modes, and preprocessing the medical images; performing region segmentation on the preprocessed medical images to obtain a region of interest corresponding to each modal medical image; obtaining a high-dimensional imaging omics feature corresponding to each region of interest; dividing the high-dimensional image omics features to obtain a training set and a test set, and performing gradient dimensionality reduction to obtain low-dimensional image omics feature tags; and training a plurality of candidate parameter models by using the low-dimensional imaging omics feature tags as a cross training data set and using different algorithms. A subject working feature curve is drawn, the area mean value under the subject working feature curve is calculated, and the area mean value with the highest area mean value is determined as the optimal parameter model, so that the image features can be effectively extracted, and medical image information can be mined to the maximum extent.

Description

technical field [0001] The invention relates to the field of medical image processing and analysis, in particular to a multimodal parameter model optimization and fusion method based on radiomics features. Background technique [0002] Radiomics is an emerging research field in recent years that aims to extract and analyze medical images to establish models that may improve the accuracy of diagnosis, prognosis, and prediction. With the development of radiomics, more researchers have gradually joined the field and discussed and improved some of them. At present, in the field of omics, radiomics has been combined with genomics to establish predictive models. [0003] Most radiomics research uses Matlab software or Python platform to extract radiomics features. Since Matlab is a semi-open source software, it is not convenient to view and modify the underlying functions, so it cannot be conveniently used by every researcher. [0004] With the popularity of artificial intellige...

AI Technical Summary

Problems solved by technology

Researchers have developed open source software platforms IBEX and QIFE in the direction of radiomics, but the content of the platform only i

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