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
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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

Example Embodiment

[0035] Example 1

[0036] figure 1 An image process method of tagging provides a schematic of the present embodiment, the image tagging method may be designated by means performs the image, the image tagging means may be implemented by software and / or hardware manner, the image tagging device may be an electronic device some or all. Wherein, the electronic device may be a personal computer (PersonalComputer, PC), such as a desktop, one machine, laptop, tablet, etc. in the present embodiment, may also be mobile phones, wearable device, PDA (Personal Digital Assistant, PDA ) and other devices. In the electronic device to perform the following description of the present subject image tagging method according to an embodiment.

[0037] Such as figure 1 , The present embodiment provides an image tagging method may include the steps S1 ~ S3:

[0038] Step S1, the image acquiring first tagging.

[0039] Step S2, the model image processing calls for the first tagging image processing, ...

Example Embodiment

[0079] Example 2

[0080] Image 6 A structural diagram of an electronic device provided in this embodiment. The electronic device includes at least one processor and a memory connected to the at least one processor. Therein, the memory stores a computer program that can be operated by the at least one processor, the computer program being performed by the at least one processor so that the at least one processor can perform the image labeling method of Example 1. . The electronic devices provided in this embodiment can be personal computers, such as desktops, integrated, laptops, tablets, etc., can also be mobile devices such as mobile phones, wearable devices, handheld computers. Image 6 The displayed electronic device 3 is merely an example and should not be restricted to the functions of the embodiments of the present invention.

[0081] The components of the electronic device 3 may include, but are not limited to, at least one processor 4, at least one memory 5, a bus 6 conne...

Example Embodiment

[0088] Example 3

[0089] This embodiment provides a computer readable storage medium stored with a computer program that implements the image labeling method of Example 1 when executed by the processor.

[0090] Among them, the readable storage medium can be used, more specific, but not limited to, portable disc, hard disk, random access memory, read-only memory, can wiping programmable read only memory, optical storage device, magnetic storage device, or any of the above Suitable combination.

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

[0092] Among them, the program code for performing the present invention can be written in any combination of one or more programming languages, the program code, can be performed c...

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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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