mrnet | ACL tear detector to spot knee injuries | Machine Learning library

by ahmedbesbes Python Version: Current 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 Artificial Intelligence, Machine Learning, Deep Learning, Pytorch 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.

The data comes from Stanford ML Group research lab. It consits of 1,370 knee MRI exams performed at Stanford University Medical Center to study the presence of Anterior Cruciate Ligament (ACL) tears.

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Support

mrnet has a low active ecosystem.

It has 76 star(s) with 31 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 6 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of mrnet is current.

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 not available. You will need to build from source code and install.

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

Installation instructions are not available. Examples and code snippets are available.

It has 1058 lines of code, 37 functions and 5 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.

Generate training dataset
Train a model
Evaluate a model
Compute the classifer features
Get the learning rate
Parse arguments

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

You can download it from GitHub.
You can use mrnet like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.