Solitary pulmonary nodules are common radiologic findings, typically discovered incidentally through chest radiography or computed tomography of the neck, chest, and abdomen. Primary care physicians must decide how to pursue an evaluation of a nodule once it has been identified. The differential diagnosis for pulmonary nodules includes benign and malignant causes. Diameter of 8 mm or more, "gro...

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based detection methods lack ability capture long-range dependencies, which is vital for global information extraction. In computer vision tasks, non-local operations widely utilized, but computational cost could very high 3D computed tomography (C...

The potential use of positron emission tomography (PET) imaging in patients with non-small cell lung cancer (NSCLC) is broadly divided into 5 categories: management of solitary pulmonary nodule, mediastinal lymph node evaluation, detection of metastases, evaluation of response to chemoradiation and detection of recurrence. The purpose of this review is to discuss the current clinical applicatio...

We are developing a computer-aided detection (CAD) system for the identification of small pulmonary nodules in screening CT scans. The main modules of our system, i.e. a dot-enhancement filter for nodule candidate selection and a neural classifier for false positive finding reduction, are described. The preliminary results obtained on the so-far collected database of lung CT are discussed.

Lung nodules are potential manifestations of lung cancer, and their early detection facilitates early treatment and improves patient’s chances for survival. For this reason, CAD systems for lung cancer have been proposed in several studies. All these works involved mainly three steps to detect the pulmonary nodule: preprocessing, segmentation of the lung and classification of the nodule candida...

Determining the change in the pulmonary nodule size is a critical measurement for cancer diagnosis and therapy evaluation. In this study, an image-processing method that quantifies the nodule volume change based on computed tomography (CT) images is proposed. The proposed method consists of the following four steps: CT image interpolation, pulmonary region segmentation, nodule extraction, and n...

PURPOSE To evaluate the effect of computer-aided diagnosis (CAD) on radiologists' detection of pulmonary nodules. MATERIALS AND METHODS Fifty chest computed tomographic (CT) examination cases were used. The mean nodule size was 0.81 cm +/- 0.60 (SD) (range, 0.3-2.9 cm). Alternative free-response receiver operating characteristic (ROC) analysis with a continuous rating scale was used to compar...