This work presents a systematic review of techniques for the 3D automatic detection of
pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze …

This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …

We investigate the problem of lung nodule malignancy suspiciousness (the likelihood of
nodule malignancy) classification using thoracic Computed Tomography (CT) images …

Lung cancer is a fatal disease with a high mortality rate in diseased patients. Early diagnosis
of this disease and accurately identifying the lung cancer stage can save the patients' lives …

Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-
aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule …

We present an approach to detect lung cancer from CT scans using deep residual learning.
We delineate a pipeline of preprocessing techniques to highlight lung regions vulnerable to …

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 …

The availability of pulmonary nodules in CT scan image of lung does not completely specify
cancer. The noise in an image and morphology of nodules, like shape and size has an …

Current computed tomography (CT) technology allows for near isotropic, submillimeter
resolution acquisition of the complete chest in a single breath hold. These thin-slice chest …

Computer aided detection (CAD) systems can assist radiologists by offering a second
opinion on early diagnosis of lung cancer. Classification and feature representation play …