  The accurate and consistent border segmentation plays an important role in
the tumor volume estimation and its treatment in the field of Medical Image
Segmentation. Globally, Lung cancer is one of the leading causes of death and
the early detection of lung nodules is essential for the early cancer diagnosis
and survival rate of patients. The goal of this study was to demonstrate the
feasibility of Deephealth toolkit including PyECVL and PyEDDL libraries to
precisely segment lung nodules. Experiments for lung nodules segmentation has
been carried out on UniToChest using PyECVL and PyEDDL, for data pre-processing
as well as neural network training. The results depict accurate segmentation of
lung nodules across a wide diameter range and better accuracy over a
traditional detection approach. The datasets and the code used in this paper
are publicly available as a baseline reference.
