# The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

arXiv: https://arxiv.org/abs/2305.08992 · HTML: https://mlsanity.com/paper/2305.08992/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 24 references that are in the map.
- First posted on arXiv 15 May 2023.

## Builds on (most cited first, 14 of 14)

- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Free-Form Image Inpainting with Gated Convolution](https://mlsanity.com/paper/1806.03589/) (2018)
- [Generative Image Inpainting with Contextual Attention](https://mlsanity.com/paper/1801.07892/) (2018)
- [The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification](https://mlsanity.com/paper/2107.02314/) (2021)
- [Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge](https://mlsanity.com/paper/1811.02629/) (2018)
- [Large Scale Image Completion via Co-Modulated Generative Adversarial Networks](https://mlsanity.com/paper/2103.10428/) (2021)
- [Why rankings of biomedical image analysis competitions should be interpreted with care](https://mlsanity.com/paper/1806.02051/) (2018)
- [Image Inpainting via Conditional Texture and Structure Dual Generation](https://mlsanity.com/paper/2108.09760/) (2021)
- [Methods and open-source toolkit for analyzing and visualizing challenge results](https://mlsanity.com/paper/1910.05121/) (2019)
- [Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient](https://mlsanity.com/paper/2103.06205/) (2021)
- [Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling](https://mlsanity.com/paper/2111.04090/) (2021)
- [Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report](https://mlsanity.com/paper/2210.12113/) (2022)
- [Approaching Peak Ground Truth](https://mlsanity.com/paper/2301.00243/) (2022)
- [Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings](https://mlsanity.com/paper/2205.10355/) (2022)

## Built on by (most cited first, 8 of 8)

- [Post-Processing Methods for Improving Accuracy in MRI Inpainting](https://mlsanity.com/paper/2510.15282/) (2025)
- [CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models](https://mlsanity.com/paper/2508.03594/) (2025)
- [Generating healthy counterfactuals with denoising diffusion bridge models](https://mlsanity.com/paper/2510.13684/) (2025)
- [POWDR: Pathology-preserving Outpainting with Wavelet Diffusion for 3D MRI](https://mlsanity.com/paper/2601.09044/) (2026)
- [VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation](https://mlsanity.com/paper/2604.22942/) (2026)
- [Local Label-Informed Feature Transfer for Generating Ground-Truth Medical Images: A Comparison of GAN- and Diffusion-Based Approaches](https://mlsanity.com/paper/2607.18882/) (2026)
- [CATCH: Counterfactual Anatomical Tissue Inpainting with Conditional Haar Diffusion](https://mlsanity.com/paper/2609.29591/) (2026)
- [Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors](https://mlsanity.com/paper/2610.08983/) (2026)

## Abstract (arXiv)

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological scan. This poses problems, as many algorithms are designed to analyze healthy brains and provide no guarantee for images featuring lesions. Examples include, but are not limited to, algorithms for brain anatomy parcellation, tissue segmentation, and brain extraction. To solve this dilemma, we introduce the BraTS inpainting challenge. Here, the participants explore inpainting techniques to synthesize healthy brain scans from lesioned ones. The following manuscript contains the task formulation, dataset, and submission procedure. Later, it will be updated to summarize the findings of the challenge. The challenge is organized as part of the ASNR-BraTS MICCAI challenge.