The computer-based process of identifying the boundaries of lung from surrounding thoracic
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …

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

Background Automated segmentation of anatomical structures is a crucial step in image
analysis. For lung segmentation in computed tomography, a variety of approaches exists …

To improve the early diagnosis and treatment of lung diseases automated lung
segmentation from CT images is a crucial task for clinical decision. The segmentation of the …

COVID-19 clinical presentation and prognosis are highly variable, ranging from
asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi …

It has been shown that employing multiple atlas images improves segmentation accuracy in
atlas-based medical image segmentation. Each atlas image is registered to the target image …

Objectives The objective of this study is to assess the performance of a computer-aided
diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution …

We present a stochastic gradient descent optimisation method for image registration with
adaptive step size prediction. The method is based on the theoretical work by Plakhov and …

A popular technique for nonrigid registration of medical images is based on the
maximization of their mutual information, in combination with a deformation field …

A scheme for the automatic detection of nodules in thoracic computed tomography scans is
presented and extensively evaluated. The algorithm uses the local image features of shape …