The use of machine learning (ML) has been increasing rapidly in the medical imaging field,
including computer-aided diagnosis (CAD), radiomics, and medical image analysis …

Artificial neural networks have featured in a wide range of medical journals, often with
promising results. This paper reports on a systematic review that was conducted to assess …

Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …

Early detection of cancer is the most promising way to enhance a patient's chance for
survival. This paper presents a computer aided classification method in computed …

Given that neural networks have been widely reported in the research community of medical
imaging, we provide a focused literature survey on recent neural network developments in …

To explore the application of neural network algorithm model in lung cancer imaging, and
provide reference for the application and development of artificial neural network (ANN) …

Purpose: The paper presents a complete computer‐aided detection (CAD) system for the
detection of lung nodules in computed tomography images. A new mixedfeature selection …

Lung nodules are small, round, or oval-shaped masses of tissue in the lung region. Early
diagnosis and treatment of lung nodules can significantly improve the quality of patients' …

When lung nodules overlap with ribs or clavicles in chest radiographs, it can be difficult for
radiologists as well as computer-aided diagnostic (CAD) schemes to detect these nodules …

We propose a new multiscale rotation-invariant convolutional neural network (MRCNN)
model for classifying various lung tissue types on high-resolution computed tomography …