MONAI | AI Toolkit for Healthcare Imaging | Machine Learning library

by Project-MONAI Python Version: 1.3.1rc8 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | MONAI Summary

MONAI is a Python library typically used in Healthcare, Pharma, Life Sciences, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. MONAI has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install MONAI' or download it from GitHub, GitLab, PyPI.

Medical Open Network for AI.

Support

Quality

Security

License

Reuse

Support

MONAI has a medium active ecosystem.

It has 4116 star(s) with 792 fork(s). There are 90 watchers for this library.

There were 3 major release(s) in the last 6 months.

There are 264 open issues and 2257 have been closed. On average issues are closed in 58 days. There are 28 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of MONAI is 1.3.1rc8

Quality

MONAI has 0 bugs and 0 code smells.

Security

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

MONAI code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MONAI is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

MONAI releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Return a dict containing the cmdclass .
Write data to a nifti file .
Calculate the image .
Wrapper for sliding window inference .
Compute the derivative of the surface .
Plots a 3D plot of a 3D volume .
Run the range test .
Load a model from mmar .
Imports a module .
Partition a dataset into multiple partitions .

Get all kandi verified functions for this library.

MONAI Key Features

No Key Features are available at this moment for MONAI.

MONAI Examples and Code Snippets

Liver Segmentation Using Monai and PyTorch,Showing a patient from the dataset

Jupyter Notebook

Lines of Code : 40

License : No License

Copy

def show_patient(data, SLICE_NUMBER=1, train=True, test=False):
    """
    This function is to show one patient from your datasets, so that you can si if the it is okay or you need 
    to change/delete something.
    `data`: this parameter should t

SALMON v.2: Segmentation deep learning ALgorithm based on MONai toolbox,Usage,Folders structure:

Python

Lines of Code : 32

License : Permissive (MIT)

Copy

.
├── Data_folder                   
|   ├── CT               
|   |   ├── 1.nii 
|   |   ├── 2.nii 	
|   |   └── 3.nii                     
|   ├── CT_labels                         
|   |   ├── 1.nii 
|   |   ├── 2.nii 	
|   |   └── 3.nii  

.
├──

Liver Segmentation Using Monai and PyTorch,Training

Jupyter Notebook

Lines of Code : 9

License : No License

Copy

model = UNet(
    dimensions=3,
    in_channels=1,
    out_channels=2,
    channels=(16, 32, 64, 128, 256), 
    strides=(2, 2, 2, 2),
    num_res_units=2,
    norm=Norm.BATCH,
).to(device)

Community Discussions

Trending Discussions on MONAI

How to get transformation affine from ITK registration?

QUESTION

How to get transformation affine from ITK registration?

Asked 2022-Mar-15 at 16:52

Given 3D MRI scans A, B, and C I want to perform an affine (co)registration of B onto A, take the transformation affine matrix of the registration and apply it on C.

My problem is that the affine matrix of the registration transform has the wrong signs. Maybe due to wrong orientation?

The TransformParameters contain 12 values of which the first 9 are the rotation matrix in row-major order and the last 3 are the translation values.

...

ANSWER

Answered 2022-Mar-11 at 19:38

Taking a look at this diff, you might be more interested in the old way of doing it. It directly constructs an ITK transform from 4x4 matrix.

But beware, I think there is a bug somewhere in this code. I added this recently and it decreased test accuracy, which makes me believe there is a bug somewhere in there.

Source https://stackoverflow.com/questions/71441883

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

Vulnerabilities

No vulnerabilities reported

Install MONAI

To install the current release, you can simply run:. For other installation methods (using the default GitHub branch, using Docker, etc.), please refer to the installation guide.
MedNIST demo and MONAI for PyTorch Users are available on Colab. Examples and notebook tutorials are located at Project-MONAI/tutorials. Technical documentation is available at docs.monai.io.