# Automated Segmentation of Ischemic Stroke Lesions in Non-Contrast Computed Tomography Images for Enhanced Treatment and Prognosis

arXiv: https://arxiv.org/abs/2411.09402 · HTML: https://mlsanity.com/paper/2411.09402/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 18 references that are in the map.
- First posted on arXiv 14 Nov 2024.

## Builds on (most cited first, 5 of 5)

- [The Medical Segmentation Decathlon](https://mlsanity.com/paper/2106.05735/) (2021)
- [nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation](https://mlsanity.com/paper/2404.09556/) (2024)
- [ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset](https://mlsanity.com/paper/2206.06694/) (2022)
- [An attempt at beating the 3D U-Net](https://mlsanity.com/paper/1908.02182/) (2019)
- [Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images](https://mlsanity.com/paper/2110.05039/) (2021)

## Built on by (most cited first, 1 of 1)

- [Towards Trustworthy Breast Tumor Segmentation in Ultrasound using Monte Carlo Dropout and Deep Ensembles for Epistemic Uncertainty Estimation](https://mlsanity.com/paper/2508.17768/) (2025)

## Abstract (arXiv)

Stroke is the second leading cause of death worldwide, and is increasingly prevalent in low- and middle-income countries (LMICs). Timely interventions can significantly influence stroke survivability and the quality of life after treatment. However, the standard and most widely available imaging method for confirming strokes and their sub-types, the NCCT, is more challenging and time-consuming to employ in cases of ischemic stroke. For this reason, we developed an automated method for ischemic stroke lesion segmentation in NCCTs using the nnU-Net frame work, aimed at enhancing early treatment and improving the prognosis of ischemic stroke patients. We achieved Dice scores of 0.596 and Intersection over Union (IoU) scores of 0.501 on the sampled dataset. After adjusting for outliers, these scores improved to 0.752 for the Dice score and 0.643 for the IoU. Proper delineation of the region of infarction can help clinicians better assess the potential impact of the infarction, and guide treatment procedures.