# Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CT

arXiv: https://arxiv.org/abs/2208.06313 · HTML: https://mlsanity.com/paper/2208.06313/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 23 references that are in the map.
- First posted on arXiv 12 Aug 2022.

## Builds on (most cited first, 11 of 11)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [SGDR: Stochastic Gradient Descent with Warm Restarts](https://mlsanity.com/paper/1608.03983/) (2016)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation](https://mlsanity.com/paper/1606.04797/) (2016)
- [Group Normalization](https://mlsanity.com/paper/1803.08494/) (2018)
- [Self-Training: A Survey](https://mlsanity.com/paper/2202.12040/) (2022)
- [Optimized U-Net for Brain Tumor Segmentation](https://mlsanity.com/paper/2110.03352/) (2021)
- [Extending nn-UNet for brain tumor segmentation](https://mlsanity.com/paper/2112.04653/) (2021)
- [Deeply-Supervised CNN for Prostate Segmentation](https://mlsanity.com/paper/1703.07523/) (2017)
- [Intracranial Hemorrhage Segmentation Using Deep Convolutional Model](https://mlsanity.com/paper/1910.08643/) (2019)
- [Dense Dilated Convolutions Merging Network for Land Cover Classification](https://mlsanity.com/paper/2003.04027/) (2020)

## Built on by (most cited first, 4 of 4)

- [Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM)](https://mlsanity.com/paper/2505.11738/) (2025)
- [Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform](https://mlsanity.com/paper/2505.09380/) (2025)
- [Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging Segmentation](https://mlsanity.com/paper/2412.19026/) (2024)
- [Adaptive Post-Processing Drives Instance-Level Detection in Stroke Lesion Segmentation](https://mlsanity.com/paper/2608.16377/) (2026)

## Abstract (arXiv)

We propose a novel and flexible attention based U-Net architecture referred to as "Voxels-Intersecting Along Orthogonal Levels Attention U-Net" (viola-Unet), for intracranial hemorrhage (ICH) segmentation task in the INSTANCE 2022 Data Challenge on non-contrast computed tomography (CT). The performance of ICH segmentation was improved by efficiently incorporating fused spatially orthogonal and cross-channel features via our proposed Viola attention plugged into the U-Net decoding branches. The viola-Unet outperformed the strong baseline nnU-Net models during both 5-fold cross validation and online validation. Our solution was the winner of the challenge validation phase in terms of all four performance metrics (i.e., DSC, HD, NSD, and RVD). The code base, pretrained weights, and docker image of the viola-Unet AI tool are publicly available at urlhttps://github.com/samleoqh/Viola-Unet.