R
Rafael Wiemker
Researcher at Philips
Publications - 162
Citations - 2393
Rafael Wiemker is an academic researcher from Philips. The author has contributed to research in topics: Segmentation & Image processing. The author has an hindex of 24, co-authored 161 publications receiving 2263 citations. Previous affiliations of Rafael Wiemker include University of Hamburg.
Papers
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Proceedings ArticleDOI
Comparative Performance Analysis for Computer Aided Lung Nodule Detection and Segmentation on Ultra-Low-Dose vs. Standard-Dose CT
TL;DR: The comparable performance of lung nodule CAD in ultra-low-dose and standard-dose images is of particular interest with respect to lung cancer screening of asymptomatic patients, and a correlation of 94% between the volume-equivalent nodule diameter as automatically measured on ultra-Low-dose versus on standard- dose images is observed, indicating that ultra- low-dose CT is also feasible for growth-rate assessment in follow-up examinations.
Patent
System and method for processing a medical image
TL;DR: In this paper, a system consisting of segmentation means (120) for applying a plurality of different segmentation methods (124) to the region of interest for obtaining an associated plurality of segmentations results (122), visualization means (140) for simultaneously displaying the plurality of results to a user, and a user input (160) for receiving from the user a selection command (162) indicative of a selection of one of the plurality segmentation results for establishing an associated one of those segmentations as a selected segmentation method (164).
Proceedings ArticleDOI
Improved sensitivity of dynamic CT with a new visualization method for radial distribution of lung nodule enhancement
TL;DR: The suggested method for measurement and visualization of contrast enhancement as radially resolved curves has reduced false negative results, and thus improved sensitivity, and proved to be a valuable tool for differential diagnosis between malignant and benign lesions using dynamic CT.
Patent
Image data segmentation
TL;DR: In this article, a 2D boundary start position corresponding to tissue of interest in a cross-section of volumetric image data is identified by a current position of a graphical pointer with respect to the crosssection.
Proceedings ArticleDOI
Toward computer-aided emphysema quantification on ultralow-dose CT: reproducibility of ventrodorsal gravity effect measurement and correction
Rafael Wiemker,Roland Opfer,Thomas Bülow,Patrik Rogalla,Amnon Steinberg,Ekta Dharaiya,Krishna Subramanyan +6 more
TL;DR: Comparing ultra-low-dose CT scans of each patient shows that measurement of the ventrodorsal gravity effect is patient specific but reproducible and can be measured and corrected in an unsupervised way using robust fitting of a linear function.