Purpose
Automate comet segmentation and consolidate reproducible measurements to accelerate reporting and audits.
Goal
Reduce manual analysis time, minimize variability, and ensure data and image traceability.
Workflow
Secure authentication, image upload, backend processing, MinIO storage, and metrics persisted in MySQL.
How to Cite
The tools available on this platform are built upon scientifically validated methods. If you use this software in your research, please cite the following publication:
Ruz-Suarez et al. (2022). Convolutional Neural Network for Segmentation of Single Cell Gel Electrophoresis Assay. In: Brito-Loeza, C. et al. (eds), Intelligent Computing Systems. ISICS 2022. Springer. https://doi.org/10.1007/978-3-030-98457-1_5
Our Team
Meet the people behind the platform
The tools on this platform were developed through an interdisciplinary collaboration bringing together expertise in clinical sciences, applied mathematics, computer science, and biomedical engineering.
Elda Leonor Pacheco Pantoja, PhD
Anáhuac Mayab University, México
Researcher and professor at the School of Medicine with over 25 years of experience in health sciences. She holds a PhD in Clinical Chemistry from the University of Liverpool, UK. Her research focuses on bone metabolism and genomic instability in chronic-degenerative diseases, and she has been recognized with the Kellogg's Research Prize and awards from the Mexican Society of Nutrition and Endocrinology.
Lavdie Rada Ülgen, PhD
Bahçeşehir University, Istanbul, Turkey
Assistant Professor in the Biomedical Engineering Department, holding a PhD in Mathematics from the University of Liverpool, UK. Her research bridges applied mathematics and biomedical imaging, with expertise in image segmentation, computer vision, and optimization methods.
Anabel Martin Gonzalez, PhD
Universidad Autónoma de Yucatán, México
Associate Professor at the Faculty of Mathematics, holding a PhD in Computer Science (Magna Cum Laude) from the Technical University of Munich, Germany. Her work spans medical imaging, neural networks, and computer vision. Member of Mexico's National System of Researchers (SNI Level I) since 2014.
Carlos Brito-Loeza, PhD
Universidad Autónoma de Yucatán, México
Researcher and professor with a PhD in Mathematics from the University of Liverpool, UK. His work sits at the intersection of applied mathematics, image processing, and artificial intelligence, with a growing focus on neural network modeling for health science applications. Member of Mexico's National System of Researchers (SNI Level I) since 2010.
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