computer aided pulmonary nodule detection has been among major research topics lately to help for early treatment of lung cancer which is the most lethal kind of cancer worldwide.some evidence suggests that periodic screening tests with the ct of patients will help in reducing the mortality rate caused by the lung cancer. acomplete and accurate computer aided diagnosis (cad) system for detectio...

Early detection of pulmonary cancer is the most promising way to enhance a patient’s chance for survival. Accurate pulmonary nodule detection in computed tomography (CT) images is a crucial step in diagnosing pulmonary cancer. In this paper, inspired by the successful use of deep convolutional neural networks (DCNNs) in natural image recognition, we propose a novel pulmonary nodule detection ap...

In this paper, a complete system for automatic lung nodule detection from Chest CT data is proposed. The proposed system includes the methods of lung segmentation and nodule detection from CT data. The algorithm for lung segmentation consists of surrounding air voxel removal, body fat/tissue identification, trachea detection, and pulmonary vessels segmentation. The nodule detection algorithm co...

Pulmonary nodule detection and characterization continue to improve with technological advancements. The noninvasive methods available for assisting in nodule detection and for characterizing nodules as benign, malignant, or indeterminate will be discussed. Evidence-based guidelines will be reviewed to help guide the appropriate management of pulmonary nodules.

Background: Pulmonary nodular excavation should firstly evoke tuberculosis or necrosis broncho-pulmonary tumor, particularly: epidermoid carcinoma. The case discussed here illustrated these difficulties in patients with rheumatoid arthritis (RA). Case Presentation: A 63-year-old woman was presented with a-three-year history of RA and a recent discovery of an excavated pulmonary nodule. Initi...

INTRODUCTION: Detection of pulmonary nodule, lung cancer screening and metastases surveillance are widely performed by chest radiograph and/ or multidetector-row CT (MDCT) in routine clinical practice. Although higher detection rate and diagnostic capability of MDCT are considered as the major advantage, higher radiation exposure than chest radiograph is also considered as the fundamental probl...

Detection of malignant lung nodules in chest radiographs is currently performed by pulmonary radiologists, potentially with the aid of CAD systems. Recent advancements in convolutional neural network (CNN) models have improved image classification and detection for many tasks, but there has been little exploration of their use for nodule detection in chest radiographs. In this paper we explore ...

Computer-aided detection (CAD) can help radiologists to detect pulmonary nodules at an early stage. In pulmonary nodule CAD systems, feature extraction is very important for describing the characteristics of nodule candidates. In this paper, we propose a novel three-dimensional shape-based feature descriptor to detect pulmonary nodules in CT scans. After lung volume segmentation, nodule candida...

A computer-aided detection (CAD) system is helpful for radiologists to detect pulmonary nodules at an early stage. In this paper, we propose a novel pulmonary nodule detection method based on hierarchical block classification. The proposed CAD system consists of three steps. In the first step, input computed tomography images are split into three-dimensional block images, and we apply entropy a...