Image labeling method, electronic equipment and storage medium

An image annotation and image technology, applied in the computer field, can solve problems such as heavy treatment tasks, unacceptable, and unrealistic, and achieve the effects of excellent performance, fast convergence speed, and faster convergence speed

Pending Publication Date: 2022-03-11
SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The easiest way is to let professionals relabel the data according to the new rules, but obviously it is extremely unrealistic and undesirable in the current environment
As the best choice of professionals, front-line clinicians, their daily treatment tasks are unimaginably heavy. In a state of physical and mental exhaustion, it is difficult to accurately label a large amount of data in a short period of time.

Method used

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  • Image labeling method, electronic equipment and storage medium
  • Image labeling method, electronic equipment and storage medium
  • Image labeling method, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] figure 1 A schematic flow chart of an image tagging method provided in this embodiment, the image tagging method can be executed by an image tagging device, the image tagging device can be implemented by software and / or hardware, and the image tagging device can be an electronic device some or all. Wherein, the electronic device in this embodiment can be a personal computer (PersonalComputer, PC), such as a desktop computer, an all-in-one computer, a notebook computer, a tablet computer, etc., and can also be a mobile phone, a wearable device, and a personal digital assistant (PDA). ) and other terminal equipment. The image tagging method provided by this embodiment will be described below with the electronic device as the execution subject.

[0037] Such as figure 1 As shown, the image tagging method provided in this embodiment may include the following steps S1-S3:

[0038] Step S1, acquiring a first labeled image.

[0039] Step S2, calling an image processing mo...

Embodiment 2

[0080] Image 6 A schematic structural diagram of an electronic device provided in this embodiment. The electronic device includes at least one processor and a memory communicatively coupled to the at least one processor. Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the image labeling method of Embodiment 1 . The electronic device provided in this embodiment may be a personal computer, such as a desktop computer, an all-in-one computer, a notebook computer, a tablet computer, etc., and may also be a terminal device such as a mobile phone, a wearable device, or a handheld computer. Image 6 The electronic device 3 shown is only an example, and should not impose any limitation on the functions and application scope of the embodiments of the present invention.

[0081] Components of the electronic device 3 may i...

Embodiment 3

[0089] This embodiment provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the image tagging method in Embodiment 1 is realized.

[0090] Wherein, the readable storage medium may more specifically include but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device or any of the above-mentioned the right combination.

[0091] In a possible implementation manner, the present invention can also be implemented in the form of a program product, which includes program code, and when the program product runs on the electronic device, the program code is used to make the electronic device execute The image labeling method of embodiment 1.

[0092] Wherein, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program ...

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PUM

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Abstract

The invention discloses an image annotation method, electronic equipment and a storage medium. The image annotation method comprises the following steps: acquiring a first annotation image; calling an image processing model to process the first annotation image, and outputting a processing result; the image processing model is obtained by training based on a second annotation image on the basis of a pre-training model, the pre-training model is obtained by training based on the first annotation image and a third annotation image, the first annotation image is an image annotated before an annotation rule changes, and the third annotation image is an image annotated before an annotation rule changes. The second annotation image is an image which is annotated after an annotation rule changes; and marking the first marking image by using the processing result according to a target area in the processing result. The image processing model is used for processing the first annotation image annotated before the annotation rule changes, the processing result is used for annotating the first annotation image again according to the target area in the processing result, and the annotation efficiency is high.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an image labeling method, electronic equipment and storage media. Background technique [0002] In recent years, AI (Artificial Intelligence, artificial intelligence) has become more and more closely related to medicine, and artificial intelligence is gradually saving doctors from the plight of heavy, repetitive and inefficient film reading. However, with the development of medical technology, some imaging standards for disease diagnosis are also being updated with the times, which means that the medical annotation data used to train the intelligent assistance system will also change accordingly. Due to the requirement of deep learning for the amount of data, a good and effective disease-aided diagnosis model often requires a large number of high-quality labeled data for training. If the imaging diagnostic criteria of each disease only change slightly, for example, for some tu...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06T7/11G06V10/46G06V10/774
CPCG06T7/11G06T2207/30204G06F18/214
Inventor 石峰曹泽红贺怿楚詹翊强
Owner SHANGHAI UNITED IMAGING INTELLIGENT MEDICAL TECH CO LTD
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