Weakly supervised segmentation of intracranial aneurysms using a 3D focal modulation UNet
Accurate identification and quantification of unruptured intracranial aneurysms (UIAs) are
essential for the risk assessment and treatment decisions of this cerebrovascular disorder …
essential for the risk assessment and treatment decisions of this cerebrovascular disorder …
Parkinson's disease detection from resting state EEG using multi-head graph structure learning with gradient weighted graph attention explanations
Parkinson's disease (PD) is a debilitating neurodegenerative disease that has severe
impacts on an individual's quality of life. Compared with structural and functional MRI-based …
impacts on an individual's quality of life. Compared with structural and functional MRI-based …
Joint chest X-ray diagnosis and clinical visual attention prediction with multi-stage cooperative learning: enhancing interpretability
As deep learning has become the state-of-the-art for computer-assisted diagnosis,
interpretability of the automatic decisions is crucial for clinical deployment. While various …
interpretability of the automatic decisions is crucial for clinical deployment. While various …
Class Activation Map-based Weakly supervised Hemorrhage Segmentation using Resnet-LSTM in Non-Contrast Computed Tomography images
SH Ramananda, V Sundaresan - arxiv preprint arxiv:2309.16627, 2023 - arxiv.org
In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-
contrast CT (NCCT) for severity assessment. Accurate automated segmentation of ICH …
contrast CT (NCCT) for severity assessment. Accurate automated segmentation of ICH …
Medical Image Segmentation of Intracranial Hemorrhage: A Review
X Shi, H **ao, D Chen, Y Wei - 2023 7th Asian Conference on …, 2023 - ieeexplore.ieee.org
Intracranial hemorrhage (ICH) is a common clinical emergency that can lead to brain
damage or death in a serious situation with extremely high disability and mortality rates. In …
damage or death in a serious situation with extremely high disability and mortality rates. In …
from Resting State EEG Using Multi-head Graph Structure Learning with Gradient Weighted Graph Attention
C Neves, Y Zeng, Y **ao¹ - … MLCN 2024, Held in Conjunction with …, 2024 - books.google.com
Parkinson's disease (PD) is a debilitating neurodegenerative disease that has severe
impacts on an individual's quality of life. Compared with structural and functional MRI-based …
impacts on an individual's quality of life. Compared with structural and functional MRI-based …
Cerebrovascular Pathology Segmentation Using Weakly Supervised Deep Learning Methods
A Rasoulian - 2023 - spectrum.library.concordia.ca
Intracranial hemorrhage (ICH) and unruptured intracranial aneurysm (UIA) are two important
cerebrovascular diseases that require prompt and precise diagnosis for effective treatment …
cerebrovascular diseases that require prompt and precise diagnosis for effective treatment …
Enhancing Visual Interpretability in Computer-Assisted Radiological Diagnosis: Deep Learning Approaches for Chest X-Ray Analysis
Z Qiu - 2024 - spectrum.library.concordia.ca
This thesis delves into the realm of interpretability in medical image processing, focusing on
deep learning's role in enhancing the transparency and understandability of automated …
deep learning's role in enhancing the transparency and understandability of automated …
Hu Moments and transformers: A breakthrough in feature extraction and classification for detecting intracranial hemorrhages in CT scans
Intracranial hemorrhage (ICH) is a medical condition that can have severe consequences if
not diagnosed and treated promptly. There are different subtypes of ICH, such as epidural …
not diagnosed and treated promptly. There are different subtypes of ICH, such as epidural …
Revolutionizing COVID-19 Diagnosis with Swin Transformer: A Comparative Study on CT Image Attention Analysisand CNN Models performance
J Yang - 2023 4th International Conference on Computer …, 2023 - ieeexplore.ieee.org
In this paper, a novel Swin Transformer-based methodology is proposed for the diagnosis of
COVID-19 utilizing computed tomography (CT) images, with the objective of enhancing …
COVID-19 utilizing computed tomography (CT) images, with the objective of enhancing …