Abstract The World Health Organization estimates that 300 million people have asthma, 210
million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to …

This work proposes a new adaptive approach to lung segmentation based on a non-
parametric adaptive active contour method (ACM) without previous training using the new …

Lung segmentation on thoracic CT images plays an important role in early detection,
diagnosis and 3D visualization of lung cancer. The segmentation accuracy, stability, and …

Abstract The World Health Organization (WHO) recently reported that the lung tumor was the
leading cause of death worldwide. In this study, a practical computer-aided diagnosis (CAD) …

The aim of the paper is to develop a region based active contour model using variational
level set function for segmentation of lung. Ultimately, segmentation of parenchyma is …

Pneumonia is a lung infection that threatens all age groups. In this paper, we use CT scans
to investigate the effectiveness of active contour models (ACMs) for segmentation of …

Novel segmentation methods based on models of deformable active contours are constantly
proposed and validated in different fields of knowledge, with the aim to make the detection of …

Segmentation is one of the most important steps in automated medical diagnosis
applications, which remains to be a difficult task. In this paper, we propose a semi …

SCoTS captures a sparse representation of shapes in an input image through a linear span
of previously delineated shapes in a training repository. The model updates shape prior over …

In this paper a minimally interactive high-throughput system which employs a color gradient
based active contour model for rapid and accurate segmentation of multiple target objects …