Pore-scale imaging and modeling has advanced greatly through the integration of Deep
Learning into the workflow, from image processing to simulating physical processes. In …

Lung cancer has one of the highest mortality rates of all cancers and poses a severe threat
to people's health. Therefore, diagnosing lung nodules at an early stage is crucial to …

Lung cancer is one of the main reasons for death in the world among both men and women,
with an impressive rate of about five million deadly cases per year. Computed Tomography …

Purpose Lung cancer has the highest death rate among all cancers in the USA. In this work
we focus on improving the ability of computer-aided diagnosis (CAD) systems to predict the …

The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

Abstract Background CADe and CADx systems for the detection and diagnosis of lung
cancer have been important areas of research in recent decades. However, these areas are …

Lung and colon cancers lead to a significant portion of deaths. Their simultaneous
occurrence is uncommon, however, in the absence of early diagnosis, the metastasis of …

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context
information of lung nodules, and the multi-view strategy has been shown to be useful for …

Automatic lung nodule detection has great significance for treating lung cancer and
increasing patient survival. This work summarizes a critical review of recent techniques for …

Refer to the literature of lung nodule classification, many studies adopt Convolutional Neural
Networks (CNN) to directly predict the malignancy of lung nodules with original thoracic …