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MLD3
brain_age_prediction
Commits
cce7d867
Commit
cce7d867
authored
Dec 10, 2018
by
hyhuang
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Updated Readme
parent
b26465f2
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README.md
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cce7d867
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@@ -25,10 +25,13 @@ optional arguments:
as opposed to concatenating all regions along the
depth channel.
--align ALIGN Set to 1 to align channels, maximizes the intersection.
Obsolete feature, will lead to a worse performance.
--numberTrials NUMBERTRIALS
Number of repeated models to run.
--padding PADDING Set this to an integer to crop the image to the brain
--padding PADDING
Set this to an integer to crop the image to the brain
and then apply `padding` amount of padding.
Obsolete feature, will lead to a worse performance.
--batchSize BATCHSIZE
Batch size to train with. Default is 4.
--pheno PHENO Specify 1 to add phenotypics to the model.
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@@ -53,10 +56,10 @@ optional arguments:
If set, dataScale cannot be specified.
--listType LISTTYPE Only valid for ABIDE and ADHD. One of strat or site.
--depthwise DEPTHWISE
Set to 1 to use depthwise convolutions for the entire network.
Set to 1 to use depthwise convolutions for the entire network.
(Untested Feature)
--skipConnection SKIPCONNECTION
Set to 1 to allow skip connection layer, add residuals
to the network (like ResNet).
to the network (like ResNet).
(Will lead to a worse performance.)
--maxRatio MAXRATIO
Ratio of max pooling in the pool_mix augmentation. Default to 0.25.
The ratio should fall within the range [0.05, 0.75] and also be a multiple of 0.05.
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@@ -65,6 +68,13 @@ optional arguments:
Ratio of augmented images versus pure average images in the pool_mix augmentation. Default to 2. Useful only when pool_mix type is selected.
--testType TESTTYPE
One of AVG, MAX. Type of validation and test file preprocessing setting used in concat augmentation. Default to AVG.
--augment AUGMENT
One of FLIP, TRANSLATE. Type of standard augmentation. Default to None.
--origSize
Size of the original sample before augmentation. One of 100, 200, 300.
If None, then all samples are used. Default to None
--pretrained
Set to 1 to use the pretrained model to test on the UKBiobank Dataset.
```
The scripts assume that you have the following directories, which you will have to create yourself:
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