ProGAN-Mammography-Calcifications

πŸ–ΌοΈ Model Description

This model is an implementation of Progressive Growing of GANs (ProGAN), meticulously trained to generate medical images of mammograms with the presence of calcifications, mainly microcalcifications.. Its objective is to synthesize realistic images for data augmentation, research, or studying complex patterns in mammograms.

This model is part of a broader research effort on the application of GANs in medical mammography imaging.

βš™οΈ Architecture Details

  • GAN Type: Progressive Growing of GANs (ProGAN)
  • Generator: The generator's architecture is defined in progan_model.py. This file includes the Generator class necessary to instantiate the model.
  • Generator Weights: The main generator weights are found in the file generator_size_512_599.pth. This is the checkpoint with the highest resolution and training epoch achieved.
  • Critic/Discriminator Weights: (Optional) The critic/discriminator weights are found in the file critic_size_512_599.pth.

πŸ“Š Training Dataset

The model was trained using the following dataset:

This model was trained exclusively on a subset of the 'VinDr-Mammogram' dataset, consisting of mammograms showcasing confirmed calcifications. The VinDr-Mammogram dataset was meticulously curated and labeled by experienced radiologists, and its labeling scheme is unique. This model was developed as part of a Bachelor's Final Project (TFG) at the University of Extremadura (UEX).

It is recommended to review the original dataset documentation for more details on its composition and characteristics.

πŸš€ How to Use This Model

Requirements

Make sure you have the following Python libraries installed:

pip install torch
pip install huggingface_hub

πŸ–ΌοΈ Example Generated Image

Generated Calcification Image MIT License

Copyright (c) 2025 Telmo

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the β€œSoftware”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED β€œAS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support