# Resource-efficient Medical Image Analysis with Self-adapting Forward-Forward Networks

arXiv: https://arxiv.org/abs/2406.14038 · HTML: https://mlsanity.com/paper/2406.14038/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 34 references that are in the map.
- First posted on arXiv 20 Jun 2024.

## Builds on (most cited first, 18 of 18)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification](https://mlsanity.com/paper/2110.14795/) (2021)
- [What is the State of Neural Network Pruning?](https://mlsanity.com/paper/2003.03033/) (2020)
- [Evolution Strategies as a Scalable Alternative to Reinforcement Learning](https://mlsanity.com/paper/1703.03864/) (2017)
- [The Forward-Forward Algorithm: Some Preliminary Investigations](https://mlsanity.com/paper/2212.13345/) (2022)
- [VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations](https://mlsanity.com/paper/2012.15029/) (2020)
- [MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis](https://mlsanity.com/paper/2010.14925/) (2020)
- [Reservoir computing approaches for representation and classification of multivariate time series](https://mlsanity.com/paper/1803.07870/) (2018)
- [The Predictive Forward-Forward Algorithm](https://mlsanity.com/paper/2301.01452/) (2023)
- [Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm](https://mlsanity.com/paper/2312.12668/) (2023)
- [Layer Collaboration in the Forward-Forward Algorithm](https://mlsanity.com/paper/2305.12393/) (2023)
- [Emergent representations in networks trained with the Forward-Forward algorithm](https://mlsanity.com/paper/2305.18353/) (2023)
- [Graph Neural Networks Go Forward-Forward](https://mlsanity.com/paper/2302.05282/) (2023)
- [A theory for the sparsity emerged in the Forward Forward algorithm](https://mlsanity.com/paper/2311.05667/) (2023)
- [Complex Mixer for MedMNIST Classification Decathlon](https://mlsanity.com/paper/2304.10054/) (2023)
- [Extending the Forward Forward Algorithm](https://mlsanity.com/paper/2307.04205/) (2023)
- [A Study of Forward-Forward Algorithm for Self-Supervised Learning](https://mlsanity.com/paper/2309.11955/) (2023)
- [One-class systems seamlessly fit in the forward-forward algorithm](https://mlsanity.com/paper/2306.15188/) (2023)

## Built on by (most cited first, 2 of 2)

- [Scalable Forward-Forward Algorithm](https://mlsanity.com/paper/2501.03176/) (2025)
- [Detection of Breast Cancer Lumpectomy Margin with SAM-incorporated Forward-Forward Contrastive Learning](https://mlsanity.com/paper/2506.21006/) (2025)

## Abstract (arXiv)

We introduce a fast Self-adapting Forward-Forward Network (SaFF-Net) for medical imaging analysis, mitigating power consumption and resource limitations, which currently primarily stem from the prevalent reliance on back-propagation for model training and fine-tuning. Building upon the recently proposed Forward-Forward Algorithm (FFA), we introduce the Convolutional Forward-Forward Algorithm (CFFA), a parameter-efficient reformulation that is suitable for advanced image analysis and overcomes the speed and generalisation constraints of the original FFA. To address hyper-parameter sensitivity of FFAs we are also introducing a self-adapting framework SaFF-Net fine-tuning parameters during warmup and training in parallel. Our approach enables more effective model training and eliminates the previously essential requirement for an arbitrarily chosen Goodness function in FFA. We evaluate our approach on several benchmarking datasets in comparison with standard Back-Propagation (BP) neural networks showing that FFA-based networks with notably fewer parameters and function evaluations can compete with standard models, especially, in one-shot scenarios and large batch sizes. The code will be available at the time of the conference.