Karl Barth

Enhanced 3-D-reconstruction algorithm for C-arm systems suitable for interventional procedures

Increasingly, three dimensional (3-D) imaging technologies are used in medical diagnosis, for therapy planning, and during interventional procedures. The authors describe the possibilities of fast 3-D-reconstruction of high-contrast objects with high spatial resolution from only a small series of two-dimensional (2-D) planar radiographs. The special problems arising from the intended use of an open, mechanically unstable C-arm system are discussed. For the description of the irregular sampling geometry, homogeneous coordinates are used thoroughly. The well-known Feldkamp algorithm is modified to incorporate corresponding projection matrices without any decomposition into intrinsic and extrinsic parameters. Some approximations to speed up the whole reconstruction procedure and the tradeoff between image quality and computation time are also considered. Using standard hardware the reconstruction of a 256/sup 3/ cube is now possible within a few minutes, a time that is acceptable during interventions. Examples for cranial vessel imaging from some clinical test installations will be shown as well as promising results for bone imaging with a laboratory C-arm system.

3D Reconstruction from Projection Matrices in a C-Arm Based 3D-Angiography System

3D reconstruction of arterial vessels from planar radiographs obtained at several angles around the object has gained increasing interest. The motivating application has been interventional angiography. In order to obtain a three-dimensional reconstruction from a C-arm mounted X-Ray Image Intensifier (XRII) traditionally the trajectory of the source and the detector system is characterized and the pixel size is estimated. The main use of the imaging geometry characterization is to provide a correct 3D-2D mapping between the 3D voxels to be reconstructed and the 2D pixels on the radiographic images.

AWOS: angiographic workstation for digital quantitative coronary angiography

The angiographic workstation (AWOS) is an extended analysis system for digital quantitative coronary angiography. It is based on the SMI 5 image processor architecture with a fast MULTIMUX bus. A 32 Bit SUN SPARC II computer with a 760 MBytes winchester system disk, a 2 GBytes fast image disk and a 128 MBytes scene memory is connected via high speed link (HSL) to HICOR IS and via ETHERNET to POLYTRON 1000 imaging system. AWOS offers the possibility to display and to process digital angiograms from digital imaging systems, and 35 mm cine images digitized by a frame-grabber from an ARRIPRO-35 cineprojector. All standard calibration and evaluation methods for quantitative coronary angiography are implemented. AWOS is operated by a (menu-in) windows technique. At present an individual digital archive for each patient is based on 525 MB streamer tape. Standardized hardcopy printouts and VHS/S-VHS(CCIR-Standard) are available.<<ETX>>

Automated biplane vessel recognition in digital coronary angiograms

Cardiac angiograms are preferably imaged jn orthogonal so-called biplane views. In such image pairs the vessels do not resemble each other to such a degree that correspondences between them can be derived directly. Direct computer matches on the basis of similarity have been used for closer angles like 15 or 20 degrees [9 In this recent study model knowledge for each of the standardized angio-projections is used to recognize the vessels in each view. After these two matches for identification the third dimension can be calculated using the fixed and known relation of the orthogonal vascular models. 1.

Intra-operative adjustment of standard planes in C-arm CT image data.

PurposeWith the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures.MethodsWe developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm’s performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction.ResultsFor the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution (

Measurement of left ventricular ejection fraction (EF) by densitometry from digital subtraction angiography

512^3

Reduction of Metal Artifacts Using a New Segmentation Approach

5123 voxel) leads also to more robust feature points and is therefore slightly better than the