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 …

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 …

While deep learning methods have demonstrated performance comparable to human
readers in tasks such as computer-aided diagnosis, these models are difficult to interpret, do …

This paper presents a systematic review of the literature focused on the lung nodule
detection in chest computed tomography (CT) images. Manual detection of lung nodules by …

Lung cancer is a deadly disease if not diagnosed in its early stages. However, early
detection of lung cancer is a challenging task due to the shape and size of its nodules …

Twin support vector machines (TSVMs) have been successfully employed for binary
classification problems. With the advent of machine learning algorithms, data have …

Classification of benign and malignant in lung nodules using chest CT images is a key step
in the diagnosis of early-stage lung cancer, as well as an effective way to improve the …

The lung tumor is among the most detrimental kinds of malignancy. It has a high occurrence
rate and a high death rate, as it is frequently diagnosed at the later stages. Computed …

Lung cancer is one of the leading causes of cancer-related deaths worldwide. To reduce the
mortality rate, early detection and proper treatment should be ensured. Computer-aided …

Lung nodule classification plays an important role in diagnosis of lung cancer which is
essential to patients' survival. However, because the number of lung CT images in current …