DeepRepViz is an interactive web tool that can be used to inspect the 3D representations learned by predictive deep learning (DL) models. It can be used to inspect a trained DL model for biases, and debug the model. The tool is intended to help improve the transparency of such DL models. The DL models can be a 'black box' and hinder their adaptation to critical decision processes (ex: medical diagnosis). This tool aims to provide a platform that developers of DL models can use to gain a better intuition about what their model is learning by visualizing its 'learned representation' of the data. It can be used to understand what the model might be basing its decisions upon.
Go through the DeepRpeViz tutorial to understand how to setup the tool with your project and use it.
This project was inspired by Google Brain's projector.tensorflow.org, but is more catering towards the medical domain and medical imaging analysis. For implementation, we heavily rely on 3D-scatter-plot from plotly.js.
This work was funded by the DeSBi Research Unit (DFG; KI-FOR 5363; Project ID 459422098), the consortium SFB/TRR 265 Losing and Regaining Control over Drug Intake (DFG; Project ID 402170461), FONDA (DFG; SFB 1404; Project ID: 414984028) and FOR 5187 (DFG; Project ID: 442075332).
@inproceedings{rane2024_deeprepviz,
title={DeepRepViz: Identifying Potential Confounders in Deep Learning Model Predictions},
author={Rane, Roshan Prakash and Kim, JiHoon and Umesha, Arjun and Stark, Didem and Schulz, Marc-André and Ritter, Kerstin},
booktitle={Medical Image Computing and Computer Assisted Intervention – MICCAI 2024},
volume={15010},
pages={186--196},
year={2024}
}