[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

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Deep Learning MIDeepSeg
Overview

MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning [MedIA or Arxiv] and [Demo]

This repository proivdes a 2D medical image interactive segmentation method for segmentation and annotation. image

  • This project was originally developed for our previous work MIDeepSeg, if you find it's useful for your research, please consider to cite the followings:

      @article{luo2021mideepseg,
            title={MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning},
            author={Luo, Xiangde and Wang, Guotai and Song, Tao and Zhang, Jingyang and Aertsen, Michael and Deprest, Jan and Ourselin, Sebastien and Vercauteren, Tom and Zhang, Shaoting},
            journal={Medical Image Analysis},
            volume={72},
            pages={102102},
            year={2021},
            publisher={Elsevier}}

2D example A visualization comparison of different distance transform methods, following GeodisTK.

Requirements

Before you can use this package for image segmentation. You should:

  • PyTorch version >=1.0.1
  • Some common python packages such as Numpy, Pandas, SimpleITK,OpenCV, pyqt5, scipy......
  • Install the GeodisTK for geodesic distance transformation.
  • Install the SimpleCRF for interactive refinement.

How to use

1, compile the requirement library:

pip install -r requirements.txt
  1. launch the GUI
cd mideepseg
python main.py

  1. load an image for segmentation. Once the image is loaded, Firstly, give some edge points by left mouse to get an initial interactions, click the Segmentation button to obtain an initial segmentation. Then, press left mouse button to give clicks in under-segmented regions, and press right mouse button to give clicks in over-segmented region. Then click the Refinement button, and the segmentation will be updated according to the interactions.

  2. Note that, the pretrained model is only trained with placenta MR-T2 data.

Acknowledgment and Statement

  • This project was designed for academic research, not for clinical or commercial use, as it's a protected patent. If you want to use it for commercial, please contact Prof. Guotai Wang.
Comments
  • AttributeError: module 'maxflow' has no attribute 'maxflow2d'

    AttributeError: module 'maxflow' has no attribute 'maxflow2d'

    Hi, Thank you for your time. When I ran the code, the UI is appeared and there is no problem setting the seed point. but when I clicked the button of segment, an error occurred:

    Traceback (most recent call last): File "G:\label_sys\MIDeepSeg-master\MIDeepSeg-master\mideepseg\gui.py", line 191, in on_segment self.graph_maker.extreme_segmentation() File "G:\label_sys\MIDeepSeg-master\MIDeepSeg-master\mideepseg\controler.py", line 182, in extreme_segmentation fix_predict = maxflow.maxflow2d(zoomed_img.astype( AttributeError: module 'maxflow' has no attribute 'maxflow2d'

    Is there any module that can replace maxflow？Looking forward to your reply, Thank you very much!

    opened by Z-TIANQI 4
  • cant‘t find the open source of BIFSeg

    cant‘t find the open source of BIFSeg

    Hi, Thank you for your time. Recently, I have read the paper of your lab about BIFseg and am very interested in this work. However, I can't open the code link in paper. I am wondering if you can send this work to me or fix the link on your website. Looking forward to your reply, Thank you very much!

    opened by NieXiuping 3
  • 3D medical image interactive segmentation interface?

    3D medical image interactive segmentation interface?

    Hello, thanks for opening source nice work.

    For 2D interactive segmentation, you offer the UI for user interaction. What about 3D medical image interactive segmentation? Is there any UI or App to check as what we see in the demo? BTW, for 2D and 3D interactive segmentation, are they using the same trained model?

    opened by yangshunDragon 3
  • some problems caused by shadow copy probably

    some problems caused by shadow copy probably

    Hi, Luo. I have some questions about your code: in controller.py : 192 self.initial_seg = pred 194 pred[pred >= 0.5] = 1 195 pred[pred < 0.5] = 0 self.initial_seg may store the references of pred,which seems to be very crucial in the refinement stage .In your code, you change pred in the sebsequent lines.I use np.array in order to get a copy of pred.Is that right?

    opened by yeyeyeping 1
  • OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized.

    OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized.

    After installing all the packages and running python main.py, I got the following error: "OMP: Error #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized. error."

    I managed to fix it by installing the nomkl package (eg. conda install nomkl). Maybe it should be added to the requirements file if others also have the same issue.

    opened by danielkovacsdeak 1
  • how to use MIDeepSeg to segment 3D tumors?

    how to use MIDeepSeg to segment 3D tumors?

    I'm very interested in your work. I want to know how to use MIDeepSeg to segment 3D tumors? As you posted on YouTube, can you share the code? Thank you very much. [email protected]

    opened by Learnshui 1
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Healthcare Intelligence Laboratory
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