Lung nodules segmentation from CT with DeepHealth toolkit

Autor:	Chaudhry, Hafiza Ayesha Hoor, Renzulli, Riccardo, Perlo, Daniele, Santinelli, Francesca, Tibaldi, Stefano, Cristiano, Carmen, Grosso, Marco, Fiandrotti, Attilio, Lucenteforte, Maurizio, Cavagnino, Davide
Rok vydání:	2022
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	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. Comment: Workshop ICIAP 2021 - Deep-Learning and High Performance Computing to Boost Biomedical Applications
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2208.00641 Zobrazit plný text záznamu View this record from Arxiv