Skip to content

Pilot model and converter for integration of radiology data into OMOP-CDM

Notifications You must be signed in to change notification settings

ABMI/Radiology-CDM

 
 

Repository files navigation

Radiology CDM ETL Module

Build Status codecov.io

Overview

Metadata extraction module of DICOM images.

How to work

RCDM-ETL_Process

  • Radiology-CDM extracts Metadata and Pixeldata from DICOM file, which is the original radiology image, and combines the data required for RCDM and stores it in DB format and converts it into CDM.

  • Just copy and paste this code into your Rstudio!
    All you have to do is just change 'path' and 'core' in DICOMHeaderList function.
    RadiologyCDM function will read all of the DICOM files under the 'path' you've specified.
    Now check the variable 'Radiology_Image_Table' and, 'Radiology_Occurrence_Table'!

  • If you want to observe result of database analysis, you can use RCDMShinyViewer function.
    All you have to do is to download 'LoincRsnaRadiologyPlaybook.csv' file which is uploaded on this github page.
    This file is a mapping table for radiolgy terminologies.

devtools::install_github('ABMI/Radiology-CDM/RadETL')
library(RadiologyCDM)
library(dplyr)
library(ParallelLogger)
library(digest)
library(shiny)
library(ggplot2)
library(DT)

#Please don't change the name of variables : 'DICOMList', 'Radiology_Occurrence_Table', 'Radiology_Image_Table', 'LoincRsnaRadiologyPlaybook'
DICOMList<-DICOMHeaderList('path to DICOM files', core = 4)
Radiology_Occurrence_Table<-radiologyOccurrenceTable(DICOMList)
Radiology_Image_Table<-radiologyImageTable(DICOMList)
LoincRsnaRadiologyPlaybook<-read.csv('LoincRsnaRadiologyPlaybook.csv')
RCDMShinyViewer(Radiology_Occurrence_Table, Radiology_Image_Table)

About

Pilot model and converter for integration of radiology data into OMOP-CDM

Resources

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 92.3%
  • R 6.2%
  • CSS 1.1%
  • Other 0.4%