This is the Part III of our Covid-19 series. In this post, we will build a model to locate infected lesions in lung CT scans.

This is the Part II of our Covid-19 series. In this post, we will build a lung segmenation model an Covid-19 CT scans.

In this post, we will build an Covid-19 image classifier on lung CT scan data. This is a Kaggle dataset, you can download the data using this link or use Kaggle API. This is the Part I of the Covid-19 Series.

Measuring foetal head circumference is one of the most accurate method to estimate gestational age after the first trimester (first three months of pregnancy). To automate this procedure, the most important step is segment the foetal head area in ultrasound images. Then we can fit an ellipse on the head area, and build a regressor using the head mask to estimate gestational age.
In this post, we will use a U-Net architecture with residual blocks to make head segmentations. U-Net performs very well on medical images. And due to its relatively compact structure, its speed is much faster than Mask-RCNN.