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

Introduction The goal of this paper is to present a critical review of major Computer-Aided
Detection systems (CADe) for lung cancer in order to identify challenges for future research …

The charge of this Joint ATS/ERS Task Force was to critically review the state-of-the-art
stereological methods in lung morphometry, provide practical guidelines for use of these …

Pulmonary fissure detection in computed tomography (CT) is a critical component for
automatic lobar segmentation. The majority of fissure detection methods use feature …

Lung cancer is the most common cause of cancer‐related death globally. Currently, lung
nodule detection and classification are performed by radiologist‐assisted computer‐aided …

The purpose of this study was to develop a fully-automated segmentation algorithm, robust
to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of …

Computed tomography (CT) is the modality of choice for imaging the lungs in vivo. Sub-
millimeter isotropic images of the lungs can be obtained within seconds, allowing the …

Abstract The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively
compares the performance of different algorithms to identify vessels in thoracic computed …

Abstract Accurate segmentation of 2-D, 3-D, and 4-D medical images to isolate anatomical
objects of interest for analysis is essential in almost any computer-aided diagnosis system or …

Computer-aided detection (CADe) of pulmonary nodules is critical to assisting radiologists in
early identification of lung cancer from computed tomography (CT) scans. This paper …