| # Description |
| A pre-trained model for breast-density classification. |
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| # Model Overview |
| This model is trained using transfer learning on InceptionV3. The model weights were fine tuned using the Mayo Clinic Data. The details of training and data is outlined in https://arxiv.org/abs/2202.08238. The images should be resampled to a size [299, 299, 3] for training. |
| A training pipeline will be added to the model zoo in near future. |
| The bundle does not support torchscript. |
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| # Sample Data |
| In the folder `sample_data` few example input images are stored for each category of images. These images are stored in jpeg format for sharing purpose. |
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| # Input and Output Formats |
| The input image should have the size [299, 299, 3]. For a dicom image which are single channel. The channel can be repeated 3 times. |
| The output is an array with probabilities for each of the four class. |
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| # Commands Example |
| Create a json file with names of all the input files. Execute the following command |
| ``` |
| python scripts/create_dataset.py -base_dir <path to the bundle root dir>/sample_data -output_file configs/sample_image_data.json |
| ``` |
| Change the `filename` for the field `data` with the absolute path for `sample_image_data.json` |
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| # Add scripts folder to your python path as follows |
| ``` |
| export PYTHONPATH=$PYTHONPATH:<path to the bundle root dir>/scripts |
| ``` |
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| # Execute Inference |
| The inference can be executed as follows |
| ``` |
| python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json configs/logging.conf |
| ``` |
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| # Execute training |
| It is a work in progress and will be shared in the next version soon. |
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| # Contributors |
| This model is made available from Center for Augmented Intelligence in Imaging, Mayo Clinic Florida. For questions email Vikash Gupta (gupta.vikash@mayo.edu). |
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| # License |
| Copyright (c) MONAI Consortium |
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|
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
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| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
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