# HC18 Grand challenge

https://hc18.grand-challenge.org/


## About the data

The data is divided into a training set of 999 images and a test set of 335 images. The size of each 2D ultrasound image is 800 by 540 pixels with a pixel size ranging from 0.052 to 0.326 mm. The pixel size for each image can be found in the csv files: ‘training_set_pixel_size_and_HC.csv’ and ‘test_set_pixel_size.csv’. The training set also includes an image with the manual annotation of the head circumference for each HC, which was made by a trained sonographer. The csv file 'training_set_pixel_size_and_HC.csv ' includes the head circumference measurement (in millimeters) for each annotated HC in the training set. All filenames start with a number. There are 999 images in the trainingset, but the filenames only go to 805. Some ultrasound images were made during the same echoscopic examination and have therefore a very similar appearance. These images have an additional number in the filename in between "_" and "HC" (for example 010_HC.png and 010_2HC.png).

Download link : https://zenodo.org/record/1327317#.Xv2xeSgzZPY
(176.5MB

stage1 : Segment the fetal head part from the input images using "Marchov Random Fields for Segmentation.ipynb"

stage 2 : Perform feature extraction on the segmented images using VGG16 model " VGG16 feature extraction from segmented images.ipynb"

stage 3 : Use deep learning model to predict the head circumference for the input image from its features using " Predicting Head Circumference.ipynb " 
          " Distribution of Head Circumference.ipynb "