Giter VIP home page Giter VIP logo

fetal-mri-segmentation's People

Contributors

alkamid avatar ellisdg avatar galdude33 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar

fetal-mri-segmentation's Issues

How to start with new data set?

Thank you for your awesome work, I have a couple of questions and I appreciate if you can elaborate more on how to use your repository. as I am new to this world of medical image analysis, some questions may sound simple but I need a kick to be able to start using your code:

  1. lets say I have a new data set of fetal MRI, what is the procedure of using your code so I could get a 3D model of the fetus structure as described in your readme.? e.g what is the order of using your .py files?
  2. the data which I have is a DICOM directory, is there any changes necessary to the dataset? e.g. cropping, changing the data before interaction with NN? any specific cross section of fetus needed as input data?
  3. I have followed the instructions for training and prediction, but it seems I cannot setup your repository in a manner that you have intended, especially, what is exactly the <config_dir> "containing the training configurations", or "config["split_dir"] = <split_dir_path> # The directory to load/save the train/val/test split files", any suggestions?

As my research project is going to build on-top of your work, I will appreciate it if you can help me. if there is a way to stay connected outside the issue page, please let me know.

Regards.

Add Test split

Currently the data is split to Train and Validation, we should add Test split (probably just one sample) for testing purpose, and check for over-fitting.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.