A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images

S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …

Salient arithmetic data extraction from brain activity via an improved deep network

N Khaleghi, S Hashemi, SZ Ardabili, S Sheykhivand… - Sensors, 2023 - mdpi.com
Interpretation of neural activity in response to stimulations received from the surrounding
environment is necessary to realize automatic brain decoding. Analyzing the brain …

Customized 2D CNN Model for the Automatic Emotion Recognition Based on EEG Signals

F Baradaran, A Farzan, S Danishvar, S Sheykhivand - Electronics, 2023 - mdpi.com
Automatic emotion recognition from electroencephalogram (EEG) signals can be considered
as the main component of brain–computer interface (BCI) systems. In the previous years …

A novel approach for automatic detection of driver fatigue using EEG signals based on graph convolutional networks

SZ Ardabili, S Bahmani, LZ Lahijan, N Khaleghi… - Sensors, 2024 - mdpi.com
Nowadays, the automatic detection of driver fatigue has become one of the important
measures to prevent traffic accidents. For this purpose, a lot of research has been conducted …

[HTML][HTML] EEG-based functional connectivity analysis of brain abnormalities: A review study

N Khaleghi, S Hashemi, M Peivandi, SZ Ardabili… - Informatics in Medicine …, 2024 - Elsevier
Several imaging modalities and many signal recording techniques have been used to study
the brain activities. Significant advancements in medical device technologies like …

PET-validated EEG-machine learning algorithm predicts brain amyloid pathology in pre-dementia Alzheimer's disease

NH Kim, U Park, DW Yang, SH Choi, YC Youn… - Scientific Reports, 2023 - nature.com
Developing reliable biomarkers is important for screening Alzheimer's disease (AD) and
monitoring its progression. Although EEG is non-invasive direct measurement of brain …

Generating personalized facial emotions using emotional EEG signals and conditional generative adversarial networks

M Esmaeili, K Kiani - Multimedia Tools and Applications, 2024 - Springer
Facial expressions are one of the most effective and straightforward ways of conveying our
emotions and intentions. Therefore, it is crucial to conduct research aimed at developing a …

Visualizing the mind's eye: a future perspective on applications of image reconstruction from brain signals to psychiatry

Z Lu - Psychoradiology, 2023 - academic.oup.com
In an era where neuroscience dances with computational advances, the power to “visualize”
one's thoughts at image-level is no longer confined to the realm of science fiction. This …

Deep learning and bayesian hyperparameter optimization: A data-driven approach for diamond grit segmentation toward grinding wheel characterization

D Sicard, P Briois, A Billard, J Thevenot, E Boichut… - Applied Sciences, 2022 - mdpi.com
Diamond grinding wheels (DGWs) have a central role in cutting-edge industries such as
aeronautics or defense and spatial applications. Characterizations of DGWs are essential to …

Qualitative Classification of Proximal Femoral Bone Using Geometric Features and Texture Analysis in Collected MRI Images for Bone Density Evaluation

M Najafi, T Yousefi Rezaii, S Danishvar, SN Razavi - Sensors, 2023 - mdpi.com
The aim of this study was to use geometric features and texture analysis to discriminate
between healthy and unhealthy femurs and to identify the most influential features. We …