Atilla Peter Kiraly

TL;DR: A convolutional neural network performs automated prediction of malignancy risk of pulmonary nodules in chest CT scan volumes and improves accuracy of lung cancer screening.

TL;DR: The authors developed an integrated airway segmentation system that draws on an adaptive region-growing algorithm and a new hybrid algorithm that uses both region growing and mathematical morphology and shows that prefiltering the image data before airways segmentation increases the robustness of both region- growing and hybrid methods.

TL;DR: A rapid, robust method for computing a set of 3-D airway-tree paths from MDCT images, which consists of a series of paths and branch structural data, suitable for quantitative airway analysis and smooth virtual navigation.

TL;DR: A semiautomatic lesion segmentation and histogram analysis approach can provide a significant reduction in interobserver variability for DCE MR imaging measurements of K(trans) when compared with manual ROI methods, whereas intraobserver reproducibility is improved to some extent.

TL;DR: In this paper, a system and method for endoscopic path planning is presented, where a target is identified in a lung, wherein the target is located in a peripheral airway of the lung.