Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Intelligent follow-up surveying method of radiation image report, system, equipment and storage medium

An imaging and reporting technology, applied in medical reports, medical images, instruments, etc., can solve the problems of radiological diagnosis and pathological diagnosis that consume a lot of manpower

Pending Publication Date: 2019-10-22
WINNING HEALTH TECHNOLOGY GROUP CO LTD
View PDF8 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an intelligent follow-up method, system, equipment and storage medium for radiological image reports in order to overcome the defect that the consistency judgment between radiological diagnosis and pathological diagnosis requires a lot of manpower in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Intelligent follow-up surveying method of radiation image report, system, equipment and storage medium
  • Intelligent follow-up surveying method of radiation image report, system, equipment and storage medium
  • Intelligent follow-up surveying method of radiation image report, system, equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] An intelligent follow-up method for radiology imaging reports such as figure 1 As shown, the intelligent follow-up methods include:

[0065] S10. Obtain a pathology report of a patient; the pathology report includes the time of the pathology report and the identity information of the patient;

[0066] S20. Obtain all image reports of the patient within a preset time period before the pathology report time according to the identity information;

[0067] S30. Extract the pathological diagnosis attributes in the pathology report and the image diagnosis attributes in each image report respectively;

[0068] S40. Match each group of pathological diagnosis attributes with the image diagnosis attributes in each image report;

[0069] S50. If the matching is unsuccessful, determine that the image diagnosis in the image report with unsuccessful matching is wrong; if the matching is successful, determine that the image diagnosis in the image report with successful matching is c...

Embodiment 2

[0082] The intelligent follow-up method of the radiographic image report of the present embodiment is further improved on the basis of Embodiment 1, as figure 2 As shown, step S30 specifically includes:

[0083] S301. Obtain a plurality of historical reports, where diagnostic attributes in the historical reports have been marked;

[0084] S302. Using the historical report as training data, and training based on a conditional random field algorithm to obtain a diagnostic attribute recognition model;

[0085] S303. Input the pathology report and the image report into the diagnosis attribute recognition model, and output the pathology diagnosis attribute and the image diagnosis attribute.

[0086] In this embodiment, the historical report is marked by the medical consultant, and the diagnostic attributes (positioning, qualitative, and the attribute relationship between positioning and qualitative) in the report text are marked out, and then based on the conditional random field...

Embodiment 3

[0088] The intelligent follow-up method of the radiographic image report of the present embodiment is further improved on the basis of Embodiment 1, as image 3 As shown, step S40 specifically includes:

[0089] S401. Obtain historical pathology reports and historical image reports with known consistency of multiple groups of diagnostic results;

[0090] S402, respectively extracting the historical pathological diagnosis attributes in each group of historical pathology reports and the historical image diagnosis attributes in the historical image reports;

[0091] S403, using each group of historical pathological diagnosis attributes and historical image diagnosis attributes as a training data, and training a diagnostic attribute matching model based on the Bert pre-training model and the Word2Vec algorithm;

[0092] S404. Input the image diagnosis attribute in each image report and the pathology diagnosis attribute in the pathology report into the diagnosis attribute matching...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an intelligent follow-up surveying method of a radiation image report, a system, equipment and a storage medium. The intelligent follow-up surveying method comprises the stepsof acquiring a pathological report of a patient, wherein the pathological report comprises a pathological report time and identity information of the patient; acquiring all image reports in a preset time period before the pathological report time according to the identity information; respectively extracting a pathological diagnosis attribute in the pathological report and an image diagnosis attribute in each image report; respectively matching each set of pathological diagnosis attributes with the image diagnosis attribute in each image report; if matching is unsuccessful, determining an error in the image diagnosis; if matching succeeds, determining a fact that the image diagnosis is correct; marking a label which represents a matching result on the image report; and performing follow-upsurveying on the corresponding patient according to the label. The intelligent follow-up surveying method realizes automatic determining for consistency between image diagnosis and pathological diagnosis, thereby realizing automatic and intelligent diagnosis to the radiation image report.

Description

technical field [0001] The invention belongs to the field of consistency judgment between radiological examination diagnosis and pathological diagnosis, and in particular relates to an intelligent follow-up method, system, equipment and storage medium for radiographic image reports. Background technique [0002] As medical X-ray machines, CT and MR and other medical radiological examination equipment become more and more mature, radiological examination has become a common clinical examination, which plays an important role in the initial screening, positioning and characterization of diseases. [0003] In radiology diagnosis, radiologists need to combine pathological diagnosis to confirm whether the imaging diagnosis is correct, so as to achieve radiology follow-up and achieve the goal of improving professional level. However, radiologists, especially radiologists in large and medium-sized medical institutions, all have The following pain points: First, the workload is huge...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G16H15/00G16H30/20G16H50/20G06K9/62
CPCG16H15/00G16H30/20G16H50/20G06F18/22
Inventor 王耀伟赵璐偲王佳皓陆佳洋周绮伟潘志君岁波钱起俊周勇
Owner WINNING HEALTH TECHNOLOGY GROUP CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products