Lung cancer is the leading cause of cancer-related mortality for males and females.
Radiation therapy (RT) is one of the primary treatment modalities for lung cancer. While …

Automatic segmentation of the lung parenchyma from computed tomography (CT) images is
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …

Objectives: Automated computational segmentation of the lung and its lobes and findings in
X-Ray based computed tomography (CT) images is a challenging problem with important …

It's been more than a year that the entire world is fighting against COVID-19 pandemic.
Starting from the Wuhan city in China, COVID-19 has conquered the entire world with its …

Background Lung region segmentation is an important stage of automated image-based
approaches for the diagnosis of respiratory diseases. Manual methods executed by experts …

Аннотация Главное отличие систем искусственного интеллекта (ИИ) от простых
автоматизированных алгоритмов заключается в способности к обучению, обобщению …

Objective We aimed to develop a deep neural network for segmenting lung parenchyma
with extensive pathological conditions on non-contrast chest computed tomography (CT) …

An accurate characterisation of tire-pavement contact stresses is important for pavement
structural analysis and performance evaluation. The demand for rapid pavement design and …

Image Segmentation performs segregation of distinct segments of an image. Lung
segmentation separate different elements of thoracic region. It is an essential prerequisite to …

Lung parenchyma segmentation is the prerequisite for an automatic diagnosis system to
analyze lung CT (computed tomography) images. However, traditional lung segmentation …