Mitotic Cell Detection
A computer vision model developed to distinguish mitotic cells from normal cells in biological images, achieving a top 5 position in a competitive challenge.
Problem Statement
Distinguishing mitotic cells from normal cells is a critical task in cellular biology. This project aims to automate this process using advanced computer vision techniques.
Implementation Details
About the Challenge
Welcome to the Mitotic Cell Detection Challenge! 🧫🔬 This competition invited data scientists and computer vision experts to develop innovative solutions for a critical task in cellular biology: distinguishing mitotic cells from normal cells in biological images.
Key Objectives
- Develop a model to accurately classify microscopic images into "Mitotic" and "Normal" classes.
- Implement innovative approaches in image processing, feature extraction, and classification techniques.
- Contribute to advancements in cellular biology and medical research.
Dataset Description
The dataset consists of high-resolution microscopic images of various cell samples. Each image is labeled as either "Mitosis" or "Normal". The data was split into:
- Training Set: Used to build machine-learning models (ground truth provided).
- Test Set: Used to evaluate performance on unseen data.
Achievement
Our team successfully conquered the initial rounds and advanced to the final round among 32 top teams. We proudly secured the 5th position in this competitive challenge.