A computer aided pulmonary nodule detection system for chest radiography is proposed. The system consists of three models, viz., lung segmentation, lung nodule candidates detection and false positive reduction. Several innovations are offered in this system. The first one is that the detection of potential lung nodule candidates is conceived as a filtering process that searches for any region w...

Lung cancer is one of the most serious cancer-related diseases in Vietnam and all over world. Early detection lung nodules can help to increase survival rate patients. Computer-aided diagnosis (CAD) systems are proposed literature for early nodules. However, current CAD based on building high-quality machine learning models a fixed dataset rather than taking into account properties which very i...

An effective automated pulmonary nodule detection system can assist radiologists in detecting lung abnormalities at an early stage. In this paper, we propose a novel pulmonary nodule detection system based on a genetic programming (GP)-based classifier. The proposed system consists of three steps. In the first step, the lung volume is segmented using thresholding and 3D-connected component labe...

background: computed tomography (ct) scan is one the most useful devices in chest imaging. ct scan can be used in mediastinal abnormality, lungs, and pleural evaluations. according to the high prevalence and different causes of pulmonary nodules, we designed this study to evaluate the prevalence and the types of pulmonary nodules in noncancerous patients who underwent chest multi-detector ct (m...

background: serum lactate dehydrogenase (ldh) concentration is an indicator for tissue injury. it may be secreted locally in many conditions. for the first time, this study was performed to investigate the value of ldh level in bronchoalveolar lavage fluid (balf) in differentiation of benign from malignant single pulmonary nodules (spns) and to assess its relationship with serum ldh levels.   m...

The first stage in computer aided pulmonary nodule detection schemes is a candidate detection step designed to provide a simplified representation of the lung anatomy, such that features like the lung wall, and large airways are removed leaving only data which has greater potential to be a nodule. Nodules which are connected to blood vessels tend to be characterized by irregular geometrical fea...

This paper presents a lung nodule detection and classification system which utilizes a combination of hand crafted and deep learning features. Hand crafted features were obtained from modified methods of bag of frequencies, and taxonomic indices. We included a robust radius estimation algorithm that resulted in an average error of 1.29 pixels. Hand crafted features were obtained from 3D low dos...