| # Description | |
| A pre-trained model for breast-density classification. | |
| # 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. | |
| # 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. | |
| # 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. | |
| # 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` | |
| # Add scripts folder to your python path as follows | |
| ``` | |
| export PYTHONPATH=$PYTHONPATH:<path to the bundle root dir>/scripts | |
| ``` | |
| # 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 | |
| ``` | |
| # Execute training | |
| It is a work in progress and will be shared in the next version soon. | |
| # 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). | |
| # License | |
| Copyright (c) MONAI Consortium | |
| 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 | |
| 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. | |