Applied Medical Informatics

The informatics group develops methods to quantitatively analyze clinical and preclinical image data in the scope of interdisciplinary research. One aim is to automate certain image segmentation or analysis steps, or at least minimize the required user input, to achieve a high level of user independence and therefore reproducibility.

Selected publications

  1. Gremse F, Grouls C, Palmowski M, Lammers T, de Vries A, Grüll H, Das M, Mühlenbruch G, Akhtar S, Schober A, and Kiessling F. Virtual elastic sphere processing enables reproducible quantification of vessel stenosis at CT and MR angiography.Radiology. 2011;260(3):709‑17.
  1. Abou-Elkacem L, Gremse F, Barth S, Hoffman RM, Kiessling F, and Lederle W. Comparison of μCT, MRI and optical reflectance imaging for assessing the growth of GFP/RFP-expressing tumors.Anticancer Res. 2011;31(9):2907‑13.
  1. Doleschel D, Mundigl O, Wessner A, Gremse F, Bachmann J, Rodriguez A, Klingmüller U, Jarsch M, Kiessling F, and Lederle W. Targeted near-infrared imaging of the erythropoietin receptor in human lung cancer xenografts.J Nucl Med. 2012;53(2):304‑11.
  1. Nazari-Jahantigh M, Wei Y, Noels H, Akhtar S, Zhou Z, Koenen RR, Heyll K, Gremse F, Kiessling F, Grommes J, Weber C, and Schober A. MicroRNA-155 promotes atherosclerosis by repressing Bcl6 in macrophages.J Clin Invest. 2012;122(11):4190‑202.
  1. Kunjachan S, Gremse F, Theek B, Koczera P, Pola R, Pechar M, Etrych T, Ulbrich K, Storm G, Kiessling F, and Lammers T. Noninvasive optical imaging of nanomedicine biodistribution.ACS Nano. 2013;7(1):252‑62.

Group members

Marius (cand. M.Sc.) applies Fractal theory to characterize tumor vessel formations in order to distinguish healthy and malignant tissue and to discover relationships between receptor expression levels and the structure of tumor vessel growth.