MRNet | PyTorch implementation of the MRNet paper | Machine Learning library

by MisaOgura Python Version: 0.0.1 License: MIT

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | MRNet Summary

MRNet is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. MRNet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However MRNet build file is not available. You can download it from GitHub.

PyTorch implementation of the paper [Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet] published by the [Stanford ML Group] It is developed for participating in the [MRNet Competition] For more info, see [Background] #background) section.

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MRNet has a low active ecosystem.

It has 27 star(s) with 7 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 5 have been closed. On average issues are closed in 12 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MRNet is 0.0.1

Quality

MRNet has 0 bugs and 0 code smells.

Security

MRNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

MRNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MRNet is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

MRNet releases are available to install and integrate.

MRNet has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

MRNet saves you 233 person hours of effort in developing the same functionality from scratch.

It has 569 lines of code, 30 functions and 12 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed MRNet and discovered the below as its top functions. This is intended to give you an instant insight into MRNet implemented functionality, and help decide if they suit your requirements.

Concatenate images
Classifier
All features
Create data loader
Create a MRNet Dataset
Print training statistics
Calculates the ROC curve for the given labels and preds
Create output directory
Create loss csv file
Batch forward backprop
Update lr_sc scheduler
Save training and validation scores to file
Load csv file
Load data from a case
Create an LR scheduler
Save the checkpoint
Evaluate a batch of models
Calculate the weights for a given dataset
Make an Adam optimizer

Get all kandi verified functions for this library.

MRNet Key Features

No Key Features are available at this moment for MRNet.

MRNet Examples and Code Snippets

No Code Snippets are available at this moment for MRNet.

Community Discussions

Trending Discussions on MRNet

numpy array type not supported?

Converting DICOM image to numpy array of shape (s, 3, 256, 256)

ValueError: only one element tensors can be converted to Python scalars

EOFError: Ran out of input (CNN model)

Can't parse arguments (deep learning tutorial using pytorch)

QUESTION

numpy array type not supported?

Asked 2020-Jul-24 at 14:58

I'm trying to copy a model I was able to follow and run through a tutorial, but this time with my own data.

I was able to convert my own MRI images to numpy arrays in the same dimensions as the arrays the tutorial data is.

I tried replacing the numpy arrays in my tutorial with my own arrays and writing my own fictional csv file for normal or abnormal (case, not case).

However when I run it, I get:

...

ANSWER

Answered 2020-Jul-24 at 14:58

You can redefining the variable with astype

Source https://stackoverflow.com/questions/63075914

QUESTION

Converting DICOM image to numpy array of shape (s, 3, 256, 256)

Asked 2020-Jul-24 at 13:34

I've got folders with MRI images in them and I'm trying to replicate the MRnet study with my own data. Their model works on 1 .npy file per subject, shape (s, 3, 256, 256), with s being number of slices for a given subject (varies between subjects).

I've looked at several different methods of solving this but none seems to work for me. Closest I have gotten was to at least convert the .dcm files to JPEG using:

...

ANSWER

Answered 2020-Jul-24 at 13:34

you could modify this section of your code:

Source https://stackoverflow.com/questions/63071607

QUESTION

ValueError: only one element tensors can be converted to Python scalars

Asked 2020-Jul-19 at 10:06

I'm following this tutorial.

I'm at the last part where we combine the models in a regression.

I'm coding this in jupyter as follows:

...

ANSWER

Answered 2020-Jul-19 at 09:49

Only a tensor that contains a single value can be converted to a scalar with item(), try printing the contents of prediction, I imagine this is a vector of probabilities indicating which label is most likely. Using argmax on prediction will give you your actual predicted label (assuming your labels are 0-n).

Source https://stackoverflow.com/questions/62978582

QUESTION

EOFError: Ran out of input (CNN model)

Asked 2020-Jul-16 at 10:38

I'm following a tutorial on how to build CNN's for MRI.

I'm attempting to train the model myself and I've got a "data" folder in the folder where the files are (downloaded from his github) but when I try to train the model I get an error.

I run this in a CMD: python train.py -t acl -p sagittal --epochs=20 --prefix_name=one

However it returns:

...

ANSWER

Answered 2020-Jul-16 at 10:38

Change lines 177 and 182 of train.py from num_workers=11 to num_workers=0 . Windows has limit on the Pickle loader.

Source https://stackoverflow.com/questions/62930669

QUESTION

Can't parse arguments (deep learning tutorial using pytorch)

Asked 2020-Jul-15 at 00:30

I'm following this tutorial.

The first scripts run fine and I have a "data" folder in the folder of my scripts containing the MRI data downloaded from MRnet.

However when it comes to the "train" script I get an error. Here's the full script and the error (using jupyter notebook):

...

ANSWER

Answered 2020-Jul-15 at 00:30

I will guess.

ArgumentParser was created to get arguments when you run it in console/terminal not Juputer

Source https://stackoverflow.com/questions/62904639

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install MRNet

The code is developed with Python 3.6.8.
Request access to the dataset on the [MRNet Competition](https://stanfordmlgroup.github.io/competitions/mrnet/) page. Unzip the archive and save it to the MRNet project root. You now should have MRNet-v1.0 data directory in the project root.
Request access to the dataset on the [MRNet Competition](https://stanfordmlgroup.github.io/competitions/mrnet/) page
Unzip the archive and save it to the MRNet project root ```terminal $ unzip -qq MRNet-v1.0.zip -d path/to/MRNet (./ if you are already in it) # Note that you will see some warnings - it seems ok to ignore it ```
You now should have MRNet-v1.0 data directory in the project root ```terminal $ cd path/to/MRNet $ tree -L 1 . ├── LICENSE.txt ├── MRNet-v1.0 ├── README.md ├── environment.yml ├── notebooks ├── scripts └── src ```

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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