Biomedical subjects

S Ludke

Publications and source records attributed to S Ludke.

4 recordsLinked to original sources

PubMed2000

Combined connectivity and a gray-level morphological filter in magnetic resonance coronary angiography.

A connectivity algorithm combined with a new gray-level morphological filter dramatically improves the segmentation of tortuous coronary arteries from 3D MRI. Small coronary arteries are segmented from the larger ventricles with a new filter. These blood vessels are segmented from the noise background with connectivity. Coronary angiograms were computed in nine datasets acquired on volunteers with 3D stack of spirals and contrast-enhanced navigator sequences by both a maximum intensity projection and surface rendering. Surface images provided depth information needed to distinguish branching arteries from crossing veins. Magn Reson Med 43:892-895, 2000.

Algorithms↗

PubMed1998

3D MR coronary artery segmentation.

Coronary arteries are segmented from the blood pool using mathematical morphology operations from a 3D magnetic resonance spiral acquisition on a continuously breathing healthy volunteer. The segmented volume is maximal intensity projected at different views to yield coronary angiograms showing the left anterior descending artery (LAD), right coronary artery (RCA), and left circumflex artery (LCX). Magnetic resonance coronary angiography provides a retrospective rotating view of the coronary artery tree that complements oblique reformatted sections.

Algorithms↗

PubMed1987

3D reconstruction of the brain from magnetic resonance images using a connectivity algorithm.

We present high resolution three dimensional (3D) connectivity, surface construction and display algorithms that detect, extract, and display the surface of a brain from contiguous magnetic resonance (MR) images. The algorithms identify the external brain surface and create a 3D image, showing the fissures and surface convolutions of the cerebral hemispheres, cerebellum, and brain stem. Images produced by these algorithms also show the morphology of other soft tissue boundaries such as the cerebral ventricular system and the skin of the patient. For the purposes of 3D reconstruction, our experiments show that T1 weighted images give better contrast between the surface of the brain and the cerebral spinal fluid than T2 weighted images. 3D reconstruction of MR data provides a non-invasive procedure for examination of the brain surface and other anatomical features.

Adult↗

PubMedDate not supplied

Two algorithms for the three-dimensional reconstruction of tomograms.

Three-dimensional (3-D) surface reconstructions provide a method to view complex anatomy contained in a set of computed tomography (CT), magnetic resonance imaging (MRI), or single photon emission computed tomography tomograms. Existing methods of 3-D display generate images based on the distance from an imaginary observation point to a patch on the surface and on the surface normal of the patch. We believe that the normalized gradient of the original values in the CT or MRI tomograms provides a better estimate for the surface normal and hence results in higher quality 3-D images. Then two algorithms that generate 3-D surface models are presented. The new methods use polygon and point primitives to interface with computer-aided design equipment. Finally, several 3-D images of both bony and soft tissue show the skull, spine, internal air cavities of the head and abdomen, and the abdominal aorta in detail.

Algorithms↗