Dagmar Kainmüller

dagmar

Research Interests

  • Image Analysis for Applications in Biology and Medicine
  • Probabilistic Graphical Models and Discrete Optimization
  • Machine Learning
  • Deformable Meshes
  • Modelling Prior Shape and Appearance Knowledge

Projects

Organization

  • CVPR Workshop BioImage Computing (with Florian Jug, Pavel Tomancak, Carsten Rother)
  • BioImage Geek Seminar Series (funded by Gene Myers, Ivo Sbalzarini, Carsten Rother)

Curriculum Vitae

Work Experience:

  • 2007-2012
  • Research Associate
  • Stefan Zachow's group at the Zuse Institute Berlin, Department for Visualization and Data Analysis
  • 2002 – 2003             
  • Research Assistant
  • Prof. Dillmann, Humanoids and Intelligence Systems Lab (now KIT), University of Karlsruhe

Education:

  • 2007-2013
  • Ph.D. in Computer Science
  • Advisor: Jan Modersitzki, Institute of Mathematics and Image Computing, University of Lübeck
  • Thesis: Deformable Meshes for Accurate Automatic Segmentation of Medical Image Data
  • 1999-2006
  • Diploma in Computer Science
  • University of Karlsruhe
  • Thesis: Level Set Segmentation of the Heart from 4D Phase Contrast MRI

Publications

D. L. Richmond, D. Kainmueller, M. Y. Yang, E. W. Myers, C. Rother:
Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation
Proc. BMVC, 2016.
BMVC Best Science Paper Award 2016

L. A. Royer, D. L. Richmond, B. Andres, D. Kainmueller:
Convexity Shape Constraints for Image Segmentation
Proc. CVPR, 2016.

L. C. Stapel, B. Lombardot, C. Broaddus, D. Kainmueller, F. Jug, E. W. Myers, N. L. Vastenhouw:
Automated detection and quantification of single RNAs at cellular resolution in zebrafish embryos
Development 143(3), pp. 540-546, 2016.

D. Richmond, D. Kainmueller, B. Glocker, C. Rother, G. Myers:
Uncertainty-Driven Forest Predictors for Vertebra Localization and Segmentation
Proc. MICCAI (N. Navab et al., eds), Lecture Notes in Computer Science 9349, Springer, pp. 653-660, 2015.

D. Kainmueller, F. Jug, C. Rother, G. Myers:
Active Graph Matching for Automatic Joint Segmentation and Annotation of C. Elegans
Proc. MICCAI (P. Golland et al., eds.), Lecture Notes in Computer Science 8673, Springer, pp. 81-88, 2014.

F. Jug, T. Pietzsch, D. Kainmueller, J. Funke, M. Kaiser, E. van Nimwegen, C. Rother, G. Myers:
Optimal Joint Segmentation and Tracking of Escherichia Coli in the Mother Machine
Proc. MICCAI BAMBI 2014 (M. J. Cardoso et al., eds.), Lecture Notes in Computer Science 8677, Springer, pp. 25-36, 2014.

F. Jug, T. Pietzsch, D. Kainmueller, G. Myers:
Tracking by Assignment Facilitates Data Curation
Proc. MICCAI IMIC 2014, Lecture Notes in Computer Science, Springer, in press, 2014.
MICCAI IMIC Best Paper Award 2014

D. Kainmueller:
Deformable Meshes for Medical Image Segmentation
Latest Research in Medical Engineering, Springer, ISBN 978-3-658-07014-4, 2014.
BVM Award 2014

D. Kainmueller, H. Lamecker, B. Weber, M. Heller, H.-C. Hege, S. Zachow:
Omnidirectional Displacements for Deformable Surfaces
Medical Image Analysis 17(4), pp. 429-441, 2013.

T.D. Nguyen, H. Lamecker, D. Kainmueller S. Zachow:
Automatic Detection and Classification of Teeth in CT Data
Proc. MICCAI (N. Ayache et al., eds.), Lecture Notes in Computer Science 7510, Springer, pp. 609-616, 2012.

M. Bindernagel, D. Kainmueller, H. Seim, H. Lamecker, S. Zachow, H.-C. Hege:
An Articulated Statistical Shape Model of the Human Knee
Proc. Bildverarbeitung für die Medizin (BVM) (H. Handels et al., eds.), Informatik aktuell, Springer, pp. 59-63, 2011.

D. Kainmueller, H. Lamecker, H. Seim, S. Zachow, H.-C. Hege:
Improving Deformable Surface Meshes through Omni-directional Displacements and MRFs
Proc. MICCAI (T. Jiang et al., eds.), Lecture Notes in Computer Science 6361, Springer, pp. 227-234, 2010.
medvis-award 2010, 3rd prize (part 1/2),
Nominated for MICCAI 2010 Young Scientist Award

H. Seim, D. Kainmueller, H. Lamecker, M. Bindernagel, J. Malinowski, S. Zachow:
Model-based Auto-Segmentation of Knee Bones and Cartilage in MRI Data
Proc. MICCAI Workshop Medical Image Analysis for the Clinic: A Grand Challenge (B. v. Ginneken et al., eds.). pp. 215-223, 2010.
2nd prize in category "Segmentation of Knee Images"

D. Kainmueller, H. Lamecker, S. Zachow:
Multi-object Segmentation with Coupled Deformable Models
Annals of the British Machine Vision Association (BMVA), Vol. 5, pp. 1-10, 2009
medvis-award 2010, 3rd prize (part 2/2)

D. Kainmueller, H. Lamecker, S. Zachow, H.-C. Hege:
An Articulated Statistical Shape Model for Accurate Hip Joint Segmentation
Proc. IEEE Engineering in Medicine and Biology Conference (EMBC). pp. 6345 - 6351, 2009.

D. Kainmueller, H. Lamecker, H. Seim, M. Zinser, S. Zachow:
Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data
Proc. MICCAI (G.-Z. Yang et al., eds.), Lecture Notes in Computer Science 5762, Springer, pp. 76-83, 2009.

D. Kainmueller, H. Lamecker, H. Seim, S. Zachow:
Multi-object Segmentation of Head Bones
MIDAS Journal, MICCAI Workshop Head and Neck Auto-Segmentation Challenge, 2009.
Winner in category "Automatic Mandible Segmentation"    

H. Seim, D. Kainmueller, M. Heller, S. Zachow, H.-C. Hege:
Automatic Extraction of Anatomical Landmarks from Medical Image Data: An Evaluation of Different Methods
Proc. IEEE Int. Symp. on Biomedical Imaging (ISBI), pp. 538-541, 2009.

H. Seim, D. Kainmueller, M. Heller, H. Lamecker, S. Zachow, H.-C. Hege:
Automatic Segmentation of the Pelvic Bones from CT Data Based on a Statistical Shape Model
Proc. Eurographics Workshop on Visual Computing for Biomedicine (VCBM) (C. Botha et al., eds.), pp 538-541, 2008.

D. Kainmueller, H. Lamecker, S. Zachow, H.-C. Hege:
Coupling Deformable Models for Multi Object Segmentation
Proc. Biomedical Simulation (ISBMS) (F. Bello et al., eds.), Lecture Notes in Computer Science 5104, Springer, pp. 69-78, 2008.

D. Kainmueller, R. Unterhinninghofen, S. Ley, R. Dillmann:
Level Set Segmentation of the Heart from 4D Phase Contrast MRI
Proc. SPIE - Volume 6914 Medical Imaging 2008: Image Processing (J. M. Reinhardt, J. P. W. Pluim, eds.), pp. 691414.1-691414.8, 2008.

D. Kainmueller, T. Lange, H. Lamecker:
Shape Constrained Automatic Segmentation of the Liver based on a Heuristic Intensity Model
Proc. MICCAI Workshop on 3D Segmentation in the Clinic: A Grand Challenge (T. Heimann at al., eds.), pp. 109-116, 2007.
Winner in category "Automatic Liver Segmentation"

 

Other Publications

T. Heimann, B. van Ginneken, M. Styner, ..., D. Kainmueller, H. Lamecker, T. Lange, ...:
Comparison and Evaluation of Methods for Liver Segmentation from CT Datasets
IEEE Transactions on Medical Imaging, 28(8), pp. 1251-1265, 2009.

J. Dworzak, H. Lamecker, J. von Berg, T. Klinder, C. Lorenz, D. Kainmueller, H. Seim, H.-C. Hege, S.Zachow:
3D Reconstruction of the Human Rib Cage from 2D Projection Images Using a Statistical Shape Model
Int. J. Computer Assisted Radiology and Surgery, 25(2), pp. 111-124, 2009.

H. Seim, D. Kainmüller, H. Lamecker, S. Zachow:
A System for Unsupervised Extraction of Orthopaedic Parameters from CT Data
GI Workshop "Softwareassistenten - Computerunterstützung für die medizinische Diagnose und Therapieplanung", Lecture Notes in Informatics 154, GI, pp. 1328-1337, 2009.

D. Kainmueller, H. Lamecker, S. Zachow, M. Heller, H.-C. Hege:
Multi-object Segmentation with Coupled Deformable Models
Proc. Medical Image Understanding and Analysis (MIUA) (S. McKenna et al., eds.), pp. 34-38, 2008.

J. Singer, M. Lienhard, H. Seim, D. Kainmueller, A. Kuss, H. Lamecker, S. Zachow, R. Menzel, J. Rybak:
Model-based autosegmentation of the central brain of the honeybee, Apis mellifera, using active statistical shape models
Proc. 1st INCF Congress of Neuroinformatics: Databasing and Modeling the Brain, 2008.