Bioinformatics BSc · Researcher in Computer Vision & Biomedical Signal Processing
- 📚 Bioinformatics undergraduate @ UMA, Spain & Research Assistant (Computational Intelligence and Image Analysis lab)
- 🖥️ Focus: Computational Learning applied to Medical Imaging. I work with Angiography Imaging and Multimodal (Neuro) MRI.
- 🛠️ Core stack: Python | PyTorch | SKImage | Scikit-Learn
- 🎓 Goal: PhD in Neurocomputation, Biomedical Imaging-related
- 📖 Other Interests: Mathematics, Probabilistic Machine Learning, Single-Cell Genomics, Fluorescence Imaging
| Repo | Summary | Tech | Stars |
|---|---|---|---|
| Hyperparameter Optimization in YOLO | Unifying framework for High-Performance Bayesian and Evolutionary hyperparameter optimization in YOLO-based models for stenosis detection. | Optuna, PyTorch |  |
| FISRG FCD Segmentation | Fuzzy Information Seeded Region Growing for Automated Lesions After Stroke Segmentation in T1 MR Brain Images. | OpenCV, Numpy |  |
| MGA-YOLO | Mask-Guided attention for Stenosis Detection in YOLO models. | PyTorch |  |
| Dyslexia EEG Characterisation | Time-Series EEG Recurrence-quantification analysis for detecting underlying neural adaptation processes in dyslexia. | Scikit-Learn, PyUNICORN |  |
Additional applied & educational work
- Malign tumour prediction from BCW dataset · classical ML → repo
- A* heuristic maze solver → repo
- Histogram-based segmentation utilities → repo
- TC Image Segmentation Analysis with Region Growing and Split & Merge Techniques → repo
- Segmentation of focal cortical dysplasia (FCD) type II lesions using YOLOv8 and PyTorch → repo
- Mario Pascual-González, “Fuzzy Information Seeded Region Growing for Automated Lesions After Stroke Segmentation in MR Brain Images”, arXiv. [code]
Show BibTeX
@article{gonzalez2023fuzzy,
title={Fuzzy Information Seeded Region Growing for Automated Lesions After Stroke Segmentation in MR Brain Images},
author={Gonz{\'a}lez, Mario Pascual},
journal={arXiv preprint arXiv:2311.11742},
year={2023}
}