Multi-modality medical image identification method and device based on deep learning

Abstract

The invention provides a multi-modality medical image identification method based on deep learning. The method includes the steps that on the basis of multi-modality medical images of a patient's part to be detected, a registration method is adopted to display the multi-modality medical images in the same three-dimensional space; on the basis of the multi-modality medical images, R-CNN is adopted to identify lesion areas in the multi-modality medical images; according to coordinates of the lesion areas in the multi-modality medical images, lesion bodies are displayed in the same three-dimensional space, and according to image blocks corresponding to diagnosed lesion areas, a dense sampling method and a CNN are adopted to obtain occurrence probabilities of various preset disease types. The invention provides a multi-modality medical image identification device based on the deep learning. The device includes a multi-modality medical image display module, a lesion area detection module, a lesion body display module and a preset disease-type occurrence probability module. According to the multi-modality medical image identification method and device, the automatic identification of the lesion areas in the medical images is achieved, and effective reference data is provided for further diagnosis by doctors.

Description

technical field [0001] The present invention relates to the field of image processing, and more specifically, to a multimodal medical image recognition method and device based on deep learning. Background technique [0002] At present, with the advent of precision medicine and the era of big data, in addition to diagnostic text information, the analysis and application of image data has become one of the more core links in clinical medicine. Medical staff manually recognize these medical images as needed to diagnose the corresponding patients. Due to the tens of thousands of medical images in the hospital every day, the workload is huge and the diagnostic efficiency is low. In order to reduce the workload of medical staff, there is an urgent need for a medical image recognition method. [0003] The Chinese invention patent "CN 104866727 A method for analyzing medical data based on deep learning and its intelligent analyzer" analyzes text diagnostic data and two-dimensional...

AI Technical Summary

Problems solved by technology

However, the invention still has the following problems: First, although the association between text information and medical image information is considered, it does not consider the relationship between the spatial positions of multiple types of medical images; second, although the image data is analyzed by a deep neural network , but the algorithm has not been improved. When the images of different sizes are input in a uniform size, a lot of information is lost, and the accuracy cannot be obtained well in actual use; third, the lack of clinical decision-making function

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