Transformers-based architectures for stroke segmentation: A review

Y Zafari-Ghadim, EA Rashed, A Mohamed… - Artificial Intelligence …, 2024 - Springer
Stroke remains a significant global health concern, necessitating precise and efficient
diagnostic tools for timely intervention and improved patient outcomes. The emergence of …

[HTML][HTML] PerfU-net: baseline infarct estimation from CT perfusion source data for acute ischemic stroke

L de Vries, BJ Emmer, CBLM Majoie… - Medical image …, 2023 - Elsevier
CT perfusion imaging is commonly used for infarct core quantification in acute ischemic
stroke patients. The outcomes and perfusion maps of CT perfusion software, however, show …

CHSNet: Automatic lesion segmentation network guided by CT image features for acute cerebral hemorrhage

B Xu, Y Fan, J Liu, G Zhang, Z Wang, Z Li… - Computers in Biology …, 2023 - Elsevier
Stroke is a cerebrovascular disease that can lead to severe sequelae such as hemiplegia
and mental retardation with a mortality rate of up to 40%. In this paper, we proposed an …

Deep learning models for ischemic stroke lesion segmentation in medical images: A survey

J Luo, P Dai, Z He, Z Huang, S Liao, K Liu - Computers in Biology and …, 2024 - Elsevier
This paper provides a comprehensive review of deep learning models for ischemic stroke
lesion segmentation in medical images. Ischemic stroke is a severe neurological disease …

APIS: a paired CT-MRI dataset for ischemic stroke segmentation-methods and challenges

S Gómez, E Rangel, D Mantilla, A Ortiz, P Camacho… - Scientific Reports, 2024 - nature.com
Stroke, the second leading cause of mortality globally, predominantly results from ischemic
conditions. Immediate attention and diagnosis, related to the characterization of brain …

Hybrid CNN-Transformer Network with Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-contrast CT Scans

H Kuang, Y Wang, J Liu, J Wang, Q Cao… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS).
Non-contrast CT (NCCT) is still a mainstream imaging modality for AIS lesion measurement …

A symmetric prior knowledge based deep learning model for intracerebral hemorrhage lesion segmentation

M Nijiati, A Tuersun, Y Zhang, Q Yuan, P Gong… - Frontiers in …, 2022 - frontiersin.org
Background: Accurate localization and classification of intracerebral hemorrhage (ICH)
lesions are of great significance for the treatment and prognosis of patients with ICH. The …

Asymmetry disentanglement network for interpretable acute ischemic stroke infarct segmentation in non-contrast CT scans

H Ni, Y Xue, K Wong, J Volpi, STC Wong… - … Conference on Medical …, 2022 - Springer
Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward
computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral …

Dynamically masked discriminator for GANs

W Zhang, H Liu, B Li, J Xie, Y Huang… - Advances in …, 2024 - proceedings.neurips.cc
Abstract Training Generative Adversarial Networks (GANs) remains a challenging problem.
The discriminator trains the generator by learning the distribution of real/generated data …

Segmenting ischemic penumbra and infarct core simultaneously on non-contrast CT of patients with acute ischemic stroke using novel convolutional neural network

H Kuang, X Tan, J Wang, Z Qu, Y Cai, Q Chen, BJ Kim… - Biomedicines, 2024 - mdpi.com
Differentiating between a salvageable Ischemic Penumbra (IP) and an irreversibly damaged
Infarct Core (IC) is important for therapy decision making for acute ischemic stroke (AIS) …