Sartorius - Cell Instance Segmentation

Description:

In this competition, you’ll detect and delineate distinct objects of interest in biological images depicting neuronal cell types commonly used in the study of neurological disorders. More specifically, you’ll use phase contrast microscopy images to train and test your model for instance segmentation of neuronal cells. Successful models will do this with a high level of accuracy.

Competition webpage

Data provided -

Training data

id - unique ID for excerpt
url_legal - URL of source - this is blank in the test set.
license - license of source material - this is blank in the test set.
excerpt - text to predict reading ease of
target - reading ease
standard_error - measure of spread of scores among multiple raters for each excerpt. Not included for test data.

Goal - Predict the final three FVC measurements for each patient, as well as a confidence value in your prediction.

Evaluation metric - root mean squared error. RMSE

Models used -

LightGBM, XGboost, TabNet

Feature engineering and selection

Images