Automatic and accurate segmentation of pulmonary nodules in CT images can help
physicians perform more accurate quantitative analysis, diagnose diseases, and improve …

Recent advances in deep learning have given rise to high performance in image analysis
operations in healthcare. Lung diseases are of particular interest, as most can be identified …

Estimating lung volume capacity is crucial in clinical medicine, especially in disease
diagnostics. However, the existing estimation methods are complex and expensive, which …

Lung cancer is the most fatal disease in recent times. Early detection of the same is very
crucial and challenging task. Therefore, proper diagnostic and treatment strategies should …

Cell nucleus segmentation is an important method that is widely used in the diagnosis and
treatment of many diseases, as well as counting and identifying the cell nucleus. The main …

One of the most important steps in lung nodule diagnosis is the automatic segmentation of
nodules irrespective of their position and size in the lung parenchyma. In this paper, we …

Background: This paper focuses on segmenting the exact location of endometriosis using
the state-of-art technique known as U-Net. Endometriosis is a progressive disorder that has …

Lung disease is one of the biggest causes of death in the world. The SARS-CoV-2 virus
causes diseases like COVID-19, and the bacteria Streptococcus sp., which causes …

Amongst the different types of cancer, lung cancer is the one with the highest mortality rate
and consequently, there is an urgent need to develop early detection methods to improve …

The urgent demand for timely identification and treatment of lung cancer is propelling
ongoing research towards harnessing the power of deep learning in conjunction with chest …