Deep learning and neurology: a systematic review
AAA Valliani, D Ranti, EK Oermann - Neurology and therapy, 2019 - Springer
Deciphering the massive volume of complex electronic data that has been compiled by
hospital systems over the past decades has the potential to revolutionize modern medicine …
hospital systems over the past decades has the potential to revolutionize modern medicine …
Deep learning for hemorrhagic lesion detection and segmentation on brain CT images
L Li, M Wei, BO Liu, K Atchaneeyasakul… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Stroke is an acute cerebral vascular disease that is likely to cause long-term disabilities and
death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) …
death. Immediate emergency care with accurate diagnosis of computed tomographic (CT) …
[HTML][HTML] Using artificial intelligence for automatic segmentation of CT lung images in acute respiratory distress syndrome
Knowledge of gas volume, tissue mass and recruitability measured by the quantitative CT
scan analysis (CT-qa) is important when setting the mechanical ventilation in acute …
scan analysis (CT-qa) is important when setting the mechanical ventilation in acute …
White matter hyperintensities segmentation using an ensemble of neural networks
White matter hyperintensities (WMHs) represent the most common neuroimaging marker of
cerebral small vessel disease (CSVD). The volume and location of WMHs are important …
cerebral small vessel disease (CSVD). The volume and location of WMHs are important …
[HTML][HTML] A new family of instance-level loss functions for improving instance-level segmentation and detection of white matter hyperintensities in routine clinical brain …
MF Rachmadi, M Byra, H Skibbe - Computers in Biology and Medicine, 2024 - Elsevier
In this study, we introduce “instance loss functions”, a new family of loss functions designed
to enhance the training of neural networks in the instance-level segmentation and detection …
to enhance the training of neural networks in the instance-level segmentation and detection …
[HTML][HTML] Automatic spatial estimation of white matter hyperintensities evolution in brain MRI using disease evolution predictor deep neural networks
MF Rachmadi, MC Valdés-Hernández, S Makin… - Medical image …, 2020 - Elsevier
Previous studies have indicated that white matter hyperintensities (WMH), the main
radiological feature of small vessel disease, may evolve (ie, shrink, grow) or stay stable over …
radiological feature of small vessel disease, may evolve (ie, shrink, grow) or stay stable over …
[PDF][PDF] 融合注意力和Inception 模块的脑白质病变端到端分割
赵欣, 王欣, 王洪凯 - Acta Optica Sinica, 2021 - researching.cn
摘要针对目前磁共振脑影像上脑白质高信号区域的自动分割存在分割精度较低和细小病灶易漏
识等问题, 提出一种融合注意力和Inception 的U-Net 分割模型. 在U-Net 的编码阶段加入 …
识等问题, 提出一种融合注意力和Inception 的U-Net 分割模型. 在U-Net 的编码阶段加入 …
Improving segmentation of objects with varying sizes in biomedical images using instance-wise and center-of-instance segmentation loss function
In this paper, we propose a novel two-component loss for biomedical image segmentation
tasks called the Instance-wise and Center-of-Instance (ICI) loss, a loss function that …
tasks called the Instance-wise and Center-of-Instance (ICI) loss, a loss function that …
A Nested attention guided UNet++ architecture for white matter hyperintensity segmentation
H Zhang, C Zhu, X Lian, F Hua - IEEE Access, 2023 - ieeexplore.ieee.org
White Matter Hyperintensity (WMH) is a common finding in Magnetic Resonance Imaging
(MRI) of patients with cerebral infarction and is associated with poor prognosis. Accurate …
(MRI) of patients with cerebral infarction and is associated with poor prognosis. Accurate …
Robustness of probabilistic u-net for automated segmentation of white matter hyperintensities in different datasets of brain mri
R Maulana, MF Rachmadi… - … Conference on Advanced …, 2021 - ieeexplore.ieee.org
White Matter Hyperintensities (WMHs) are neu-roradiological features often seen in T2-
FLAIR brain MRI as white regions (ie, hyperintensities) and characteristic of small vessel …
FLAIR brain MRI as white regions (ie, hyperintensities) and characteristic of small vessel …