/Image-Segmentation-U-Net-for-automated-Nucleus-detection

This repo U-Net implementation to automate Nucleus detection using Image segmentation

Primary LanguageJupyter Notebook

Image-Segmentation-U-Net-for-automated-Nucleus-detection

This repo U-Net implementation to automate Nucleus detection using Image segmentation

Dataset

Part of Kaggle's 2018 Data Sciene Bowl

https://www.kaggle.com/c/data-science-bowl-2018

Problem statement

Spot Nuclei. Speed Cures. Imagine speeding up research for almost every disease, from lung cancer and heart disease to rare disorders. The 2018 Data Science Bowl offers our most ambitious mission yet: create an algorithm to automate nucleus detection.

We’ve all seen people suffer from diseases like cancer, heart disease, chronic obstructive pulmonary disease, Alzheimer’s, and diabetes. Many have seen their loved ones pass away. Think how many lives would be transformed if cures came faster.

By automating nucleus detection, you could help unlock cures faster—from rare disorders to the common cold. Want a snapshot about the 2018 Data Science Bowl? View this video.

Alot of the work in this notework was provided by Kjetil Åmdal-SævikKeras who made the "U-Net starter - LB 0.277" the top rated Kernel on Kaggle. https://www.kaggle.com/keegil/keras-u-net-starter-lb-0-277