Projects
Anomaly Detection
Framework to localize structural brain anomalies in fetal MRI images through the use of unsupervised learning models with the goal of assistive diagnosis.
- Deep learning
- MRI processing
- Python
MRI Super Resolution Segmentation
Domain adaptation method to adapt a relative low resolution segmenting model to a higher resolution dataset regarding the subplate (SP), cortical plate (CP) and inner plate from fetal MRI scans.
- Deep learning
- MRI processing
- Python
Binaural Beats on Cognitive States
Framework to process and analyze EEG data to extract significant biomarkers to understand the influence of binaural sound on cognitive states.
- Data processing
- EEG
- Matlab
BCI Channel Selection
Conduct and evaluation of the influence PCA and sequential selection algorithms for channel selection in an electroencephalography (EEG) signal pre-processing on the accuracy of motion imagery classification for a multi-layer perceptron (MLP) and Convolutional Neural Network (CNN) classifiers.
- Deep learning
- EEG
- BCI
- Python
BCI P300 Classifier
- Part of BR4IN.io
- Github
- Presentation
Evaluation of different machine learning (ML) and deep learning (DL) classifiers for P300 signals in a target vs non-target paradigm.
- Deep learning
- EEG
- BCI
- Python
Visible Light CT Processor
Tissue detection shown on the image based on it's intensity, and segments foreign bodies found on the image. Project for Medical Image Processing course at Tec de Monterrey.
- Image Processing
- Matlab
