README.md

In ABMI/RadiologyFeatureExtraction: Feature Extraction for Radiology data

RadiologyFeatureExtraction

Requirements

• A database in Common Data Model version 5 in one of these platforms: SQL Server, Oracle, PostgreSQL, IBM Netezza, Apache Impala, Amazon RedShift, or Microsoft APS.
• R version 3.5.0 or newer
• On Windows: RTools
• Java (openjdk 1.8 recommended)
• 25 GB of free disk space

See this video for instructions on how to set up the R environment on Windows.

Learning Requirements

• Python 3
• Minimum RAM (this is sampleCT data only): 16.0 GB (32.0 GB recommended)
• Keras, Tensorflow

How to run

1. In R, use the following code to install the dependencies:

```R library(devtools) install_github("ohdsi/SqlRender", ref = "v1.5.2") install_github("ohdsi/DatabaseConnector", ref = "v2.2.0")

#Install EBImage source("http://bioconductor.org/biocLite.R") biocLite("EBImage") ```

If you experience problems on Windows where rJava can't find Java, one solution may be to add args = "--no-multiarch" to each install_github call, for example:

R install_github("ohdsi/SqlRender", args = "--no-multiarch")

Alternatively, ensure that you have installed both 32-bit and 64-bit JDK versions, as mentioned in the video tutorial.

1. If you want to use Sample CT provided by this project, please use the code below.

R load(file.path(getwd(), 'extra/sampleCT.rda'))

Sample CT data is in nifti format, and both the image width and height are 128.

ABMI/RadiologyFeatureExtraction documentation built on May 25, 2019, 3:59 a.m.