Advances of deep learning in electrical impedance tomography image reconstruction
T Zhang, X Tian, XC Liu, JA Ye, F Fu, XT Shi… - … in Bioengineering and …, 2022 - frontiersin.org
Electrical impedance tomography (EIT) has been widely used in biomedical research
because of its advantages of real-time imaging and nature of being non-invasive and …
because of its advantages of real-time imaging and nature of being non-invasive and …
Robust electrical impedance tomography for biological application: a mini review
Electrical impedance tomography (EIT) has been used by researchers across several areas
because of its low-cost and no-radiation properties. Researchers use complex conductivity …
because of its low-cost and no-radiation properties. Researchers use complex conductivity …
An explainable machine learning pipeline for stroke prediction on imbalanced data
Stroke is an acute neurological dysfunction attributed to a focal injury of the central nervous
system due to reduced blood flow to the brain. Nowadays, stroke is a global threat …
system due to reduced blood flow to the brain. Nowadays, stroke is a global threat …
Automated stroke prediction using machine learning: an explainable and exploratory study with a web application for early intervention
Stroke is a dangerous medical disorder that occurs when blood flow to the brain is disrupted,
resulting in neurological impairment. It is a big worldwide threat with serious health and …
resulting in neurological impairment. It is a big worldwide threat with serious health and …
MMV-net: A multiple measurement vector network for multifrequency electrical impedance tomography
Multifrequency electrical impedance tomography (mfEIT) is an emerging biomedical imaging
modality to reveal frequency-dependent conductivity distributions in biomedical applications …
modality to reveal frequency-dependent conductivity distributions in biomedical applications …
Evaluation of blood biomarkers and parameters for the prediction of stroke survivors' functional outcome upon discharge utilizing explainable machine learning
Despite therapeutic advancements, stroke remains a leading cause of death and long-term
disability. The quality of current stroke prognostic models varies considerably, whereas …
disability. The quality of current stroke prognostic models varies considerably, whereas …
Unveiling the potential of machine learning approaches in predicting the emergence of stroke at its onset: a predicting framework
SL JM, SP - Scientific Reports, 2024 - nature.com
A stroke is a dangerous, life-threatening disease that mostly affects people over 65, but an
unhealthy diet is also contributing to the development of strokes at younger ages. Strokes …
unhealthy diet is also contributing to the development of strokes at younger ages. Strokes …
Towards continuous EIT monitoring for hemorrhagic stroke patients
The practical implementation of continuous monitoring of stroke patients by Electrical
Impedance Tomography (EIT) is addressed. In a previous paper, we have demonstrated EIT …
Impedance Tomography (EIT) is addressed. In a previous paper, we have demonstrated EIT …
Fast iterative shrinkage-thresholding algorithm with continuation for brain injury monitoring imaging based on electrical impedance tomography
X Liu, T Zhang, J Ye, X Tian, W Zhang, B Yang, M Dai… - Sensors, 2022 - mdpi.com
Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for
real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring …
real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring …
Multifrequency magnetic induction tomography for hemorrhagic stroke detection using an adaptive threshold split bregman algorithm
T Zhang, W Zhang, X Liu, M Dai, Q Xuan… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Magnetic induction tomography (MIT) is viewed as a promising method for brain imaging.
Most MIT studies are based on time-difference imaging, which cannot be used for detecting …
Most MIT studies are based on time-difference imaging, which cannot be used for detecting …