论文标题
使用DeepHealth Toolkit的CT分割肺结节分割
Lung nodules segmentation from CT with DeepHealth toolkit
论文作者
论文摘要
准确且一致的边界分割在肿瘤体积估计及其在医疗图像分割领域中的处理中起着重要作用。在全球范围内，肺癌是死亡的主要原因之一，肺结节的早期发现对于早期癌症诊断和患者的存活率至关重要。这项研究的目的是证明DeepHealth Toolkit的可行性，包括PYECVL和PYEDDL库，以精确的肺结节。使用PYECVL和PYEDDL在UnitoChest上进行了肺结节分割的实验，以进行数据预处理以及神经网络培训。结果描述了在较宽的直径范围内对肺结节的准确分割，并且在传统检测方法中的准确性更好。本文中使用的数据集和代码可作为基线参考公开提供。
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.
