# Deep Learning for Hemorrhagic Lesion Detection and Segmentation on Brain CT Images

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-for-hemorrhagic-lesion-detection-and-segmentation-on-brain-ct/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Lu Li,Wei Meng,Bo Liu,Kunakorn Atchaneeyasakul,Fugen Zhou,Zehao Pan,Shimran A. Kumar,Jason Zhang,Yuehua Pu,David S. Liebeskind,Fabien Scalzo |
| Citations | 169 |
| DOI | 10.1109/jbhi.2020.3028243 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3090878720 |
| PMID | 33001810 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Lu Li](https://scholariq.org/researchers/lu-li-2/)

## Paper journal

- [IEEE Journal of Biomedical and Health Informatics](https://scholariq.org/journals/ieee-journal-of-biomedical-and-health-informatics/)

## Paper primary topic

- [Acute Ischemic Stroke Management](https://scholariq.org/topics/acute-ischemic-stroke-management/)

## Paper topics

- [Acute Ischemic Stroke Management](https://scholariq.org/topics/acute-ischemic-stroke-management/)
- [Intracerebral and Subarachnoid Hemorrhage Research](https://scholariq.org/topics/intracerebral-and-subarachnoid-hemorrhage-research/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.