Code for Recurrent Mask Refinement for Few-Shot Medical Image Segmentation (ICCV 2021).

Related tags

Deep Learning RP-Net
Overview

License CC BY-NC-SA 4.0 Python 2.7 Python 3.7

Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

Steps

  1. Install any missing packages using pip or conda

  2. Preprocess each dataset using utils/preprocess

  3. Run notebooks/prepare_data_for_few_shot_learning.ipynb to generate files containing the range of each organ

Train

Test

Configure the yaml. An example is at yamls/example.yml. Change ckpt to trained model checkpoint python test.py test --yaml $PATH_TO_YAML

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Comments
  • Ask for codes

    Ask for codes

    Dear autor: Last week, I read your paper published on 2021 ICCV, called “Recurrent Mask Refinement for Few-Shot Medical Image Segmentation”. This paper is quite interesting, and I want to conduct some research based on your work. I am trying to run the code published on your GitHub and have some difficulties as follows:

    1. I followed the instructions of readme file, the file

    “prepare_data_for_few_shot_learning.ipynb” can’t be found in the published code.

    1. I attempted to run test_rpnet.py, a bug came out as : the folder "/ home / haotang / workspace / data / abdomen" cannot be found.

    2. there is no train.py in the published code.

    Could you please share the abovementioned files with me?

    Thank you for taking the time to read my question, and I’m looking forward to your reply.

    opened by CXEa 2
  • code problem

    code problem

    corr = corr.view(batch, ht, wd, 1, ht, wd) corr = corr / torch.sqrt(torch.tensor(dim).float()) corr = corr.view(-1, 1, ht, wd)

    Thank you very much for your work , but I did not understand this part of the code.Can you tell me ? Thank you.

    opened by starryFelix 0
Owner
XIE LAB @ UCI
XIE LAB @ UCI
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