Dipl.-Inf. Univ. Lorenz König /køːniɡ̊/

Natural languages:	New High German (first language), Modern English, Modern French
Contact:	koenil01‹аτ›nyumc.org +1 (212) 26-33258
Current location:	Center for Health Informatics and Bioinformatics NYU Medical Center 227 East 30th Street, 7th floor New York, NY 10016 USA

Current Projects

Collaborative Approaches to Image Analysis

Manual and semi-automatic segmentation still playing a con­sider­able role in medical image analysis, the col­labo­ration of more than one human observer (segmen­tor) may be desir­able for several reasons, in­clud­ing split-up of work­load, re­view of re­sults by a more ex­peri­enced ob­server, and esti­ma­tion of multi-observer vari­abil­ity. To this end, a frame­work is current­ly being de­signed, al­low­ing for manage­ment of ori­ginal image data as well as multi­ple users’ contri­butions, and sup­port­ing con­soli­dation into a con­census along with an esti­mate of its un­cer­tain­ty. A proto­type of a such frame­work is being im­ple­mented, in­clud­ing basic segmen­tation tools, thus cre­­­at­ing the foun­da­tions for further re­fine­ment of col­labo­rative ap­proaches.

Analysis of Sub-Voxel Edge Localization Errors in Non-Ideal Modalities

Conventional sub-voxel edge detectors act on the as­sump­tion of a box-shaped voxel aper­ture, or, using an equivalent formulation, point spread function (PSF). This assumtion is quite well fulfilled by industrial digital optical cameras, thus not having been an issue in the ap­pli­ca­tion of sub-pixel edge detectors which in the beginning was focused on aerial imaging and materials testing. However, modalities like MRI have a significantly non-box voxel aper­ture, a fact that results in sys­tem­atic edge localization errors (which we might call “edge ab­er­ra­tion”). First results show that by an analysis and simple correction of these errors, edge lo­cali­za­tion can be improved by about half an order of magnitude.

see also: details below

Development of the “PaCaSe” Software

Originating from some of my student research projects (see below), the PaCaSe software (“Patellar Cartilage Segmentation”) has been of great help to its users. It has hence been extended, now also comprising tools for thickness analysis and visualization and featuring input/output for a variety of data formats. PaCaSe will be superseded by the new collaborative framework (see above).

see also: Semi-Automatic Patellar Cartilage Segmentation

Publications

	L. König, J. M. Raya Garcia del Olmo Edge Aberration in MRI. Correction of Dislocations in Sub-Voxel Edge Detection—a Proof of Concept Proc. of Bildverarbeitung für die Medizin (BVM 2011), Lübeck, Germany, March 2011. The original publication is available online at www.springerlink.com. (bib)
	A. Horng, J. M. Raya Garcia del Olmo, M. Zscharn, L. König, M. Notohamiprodjo, M. Pietschmann, U. Hoehne-Hückstädt, I. Hermanns, U. Glitsch, R. Ellegast, K. G. Hering, M. Reiser, Ch. Glaser Locoregional Deformation Pattern of the Patellar Cartilage After Different Loading Types—High-Resolution 3D-MRI Volumetry at 3 T in-vivo Fortschr Röntgenstr. 2010; 182:1–9 (bib)
	J. M. Raya Garcia del Olmo, A. Horng, L. König, M. Reiser, Ch. Glaser Detecting Statistically Significant Changes in Cartilage Thickness with Sub-Voxel Precision Proceedings of the 18th congress of the International Society for Magnetic Resonance in Medicine (ISMRM 2010), Stockholm, Sweden. Presentation 3192, electronic poster session “Meniscus & Cartilage” (bib)
	L. König, M. Groher, A. Keil, Ch. Glaser, M. Reiser, N. Navab Semi-Automatic Segmentation of the Patellar Cartilage in MRI Proc. of Bildverarbeitung für die Medizin (BVM 2007), Munich, Germany, March 2007. The original publication is available online at www.springerlink.com. (bib)
	S. Nissen-Meyer, L. König, M. Reiser Maintaining Database Consistency in an Integrated, Heterogeneous HIS-RIS-PACS Environment Proceedings of the 17th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS 2003), London, UK, 25–28 June 2003 (bib)

Student Research Projecs

Diplomarbeit “Digital Tomosynthesis in X-Ray Phase Contrast Imaging” at ESRF
on the applicability of the principle and notably the algorithms of digital tomosynthesis on the emerging imaging technique of x-ray phase contrast
advisors: Alberto Bravin, Paola Coan, Tobias Lasser (2008/2009)

SEP “Assessment of Knee Cartilage Thickness using Magnetic Resonance Imaging”
advisor: Ben Glocker (2007)

IDP “Development and Implementation of a User-Friendly Tool for Analysis of the Patella Cartilage Using Magnetic Resonance Tomography”
advisor: Martin Groher et al. (2006/2007)

Sub-voxel Edge Detection in Non-ideal Modalities

Detail of cylindrical phantom imaged in MRI slices perpen­dicular to phantom’s cylindrical axis. Six acqui­sitions, phantom moved to the right by 0.1 mm in-plane after each acqui­sition.
Extracted edge of the phantom for each of the six dif­fer­ent acqui­sitions, indicated by dif­fer­ent colors.
Background: acquisition in which the phantom was in rightmost position.
Fig. 1. edge as identi­fied by the original edge detector for each of the six acqui­sitions.
Fig. 2. same as fig. 1, but edge modified by heuristic correction.
More consistent shape of the edge in dif­fer­ent positions quali­ta­tively demons­trates improved edge precision after correction.

Fig. 1. Uncorrected Edges (click image to enlarge)

Fig. 2. Correction applied, otherwise same as fig. 1. (click image to enlarge)