Half a century ago, the term “computer-aided diagnosis”(CAD) was introduced in the
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …

Over the last decade, deep learning (DL) has contributed to a paradigm shift in computer
vision and image recognition creating widespread opportunities of using artificial …

Subsolid pulmonary nodules occur less often than solid pulmonary nodules, but show a
much higher malignancy rate. Therefore, accurate detection of this type of pulmonary …

This paper describes a framework for establishing a reference airway tree segmentation,
which was used to quantitatively evaluate 15 different airway tree extraction algorithms in a …

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 …

This paper introduces a new, efficient, probabilistic algorithm for the automatic analysis of
3D medical images. Given an input CT volume our algorithm automatically detects and …

Segmentation of the pulmonary lobes is relevant in clinical practice and particularly
challenging for cases with severe diseases or incomplete fissures. In this work, an …

Significant work has been done towards deep learning (DL) models for automatic lung and
lesion segmentation and classification of COVID-19 on chest CT data. However …

This paper presents a method for airway tree segmentation that uses a combination of a
trained airway appearance model, vessel and airway orientation information, and region …

Chronic obstructive pulmonary disease (COPD) is a common lung disease, and quantitative
CT-based bronchial phenotypes are of increasing interest as a means of exploring COPD …