DeepSTEMI
A Novel Deep Learning System for STEMI Prognostic Prediction from Multi-Sequence Cardiac Magnetic Resonance
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User Guide
Prediction Objective:
2-Year MACE Event Probability Prediction from Multi-Sequence Cardiac Magnetic Resonance
File Format Requirements:
Image: JPG(.jpg)/PNG(.png). DICOM/NII images need to be converted into JPG/PNG format before being uploaded.
Table: Excel file, xls/xlsx
File Preparation:
Make a parent-folder with 4 required child-folders (all in
lower case
):
cine
: images from the CINE sequence (For the cine images, group 30 frames as one slice.)
lge
: images from the LGE sequence
t2
: images from the T2 sequence
tab
: table of case information (Excel .xlsx file), including 5 required columns:
name
age
sex
: 0 for female, 1 for male
grace
killip
The filenames of the images should be numbered sequentially, such as
093-img-00012-00241.jpg
093-img-00012-00242.jpg
093-img-00012-00243.jpg
093-img-00012-00244.jpg
093-img-00012-00245.jpg
Compress the parent-folder into a zip file before uploading.
Here is an example for demonstration:
Download the
demo1.zip
.
If the default name of downloaded file is
_static_gbdt_file_demo1.zip
, unzip the download file.
You will get a
demo1
directory with 4 sub-directories metioned above.
Zip the
demo1
directory into a zip file like
demo1.zip
before upload it.
Please upload the zip file and perform subsequent operations as instructed below.
Click here to upload the zip file
Upload
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