Medical image labeling method and device for deep learning

A medical imaging and deep learning technology, applied in medical imaging, informatics, healthcare informatics, etc., can solve problems such as insufficient information utilization, failure to meet the required information utilization, etc., to improve labeling efficiency and ensure labeling The effect of precision
CN110993064AActive Publication Date: 2020-04-10BEIJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING UNIV OF POSTS & TELECOMM
Publication Date
2020-04-10

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Abstract

The invention discloses a medical image labeling method and device for deep learning, and the method comprises the following steps: carrying out the preprocessing of an inputted image diagnosis report, electronic medical record information and a medical image, and generating data comprising the medical image and the extracted related diagnosis information, wherein the medical image is pre-annotated based on deep learning, the image is segmented based on an image semantic segmentation technology to obtain a boundary range of each lesion area, pixel-level segmentation annotation is performed onthe image, and classification annotation is performed on a disease type to which the image belongs based on an image classification technology in combination with image related diagnosis information;and displaying the pre-annotated image and the related diagnosis information through an interface to receive an interactive instruction for a doctor to finely adjust a pre-annotated image result, andexporting an annotation result. According to the method, the labeling efficiency is improved, and the labeling precision is ensured.
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Description

technical field

[0001] The invention relates to the technical field of image labeling, in particular to a deep learning-oriented medical image labeling method and device. Background technique

[0002] With the rapid development of medical imaging inspection equipment and the wide application of PACS systems, various types of medical image big data have been acquired and stored, making medical image analysis based on artificial intelligence a current research hotspot. In recent years, artificial intelligence algorithms have been applied in the field of medical imaging-aided diagnosis, and have achieved many remarkable results. Supervised artificial intelligence algorithms usually require a large amount of labeled data for training. How to efficiently obtain a large amount of high-quality labeled data for deep learning algorithms is an urgent problem to be solved.

[0003] Related technologies, (1) A method and device for extracting fundus image annotations. The method inclu...

Claims

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