Dr.-Ing. Christian Kier

Former Research Associate

Publications

2009

  • Kier, C., Seidel, G., Brüggemann, N., Hagenah, J., Klein, C., Aach, T. and Mertins, A.: Ultraschall zur Früherkennung von Parkinson in Medizinische Bildverarbeitung und Mustererkennung, vol. P154, pp. 1241–1248, Lecture Notes in Informatics, Lübeck, Oct., 2009
    BibTeX
    @INPROCEEDINGS{Kier2009,
      author = {Christian Kier and G{\"u}nter Seidel and Norbert Br{\"u}ggemann and Johann Hagenah and Christine Klein and Til Aach and Alfred Mertins},
      title = {Ultraschall zur Früherkennung von Parkinson},
      booktitle = {Medizinische Bildverarbeitung und Mustererkennung},
      year = {2009},
      month = {Oct.},
      series = {Lecture Notes in Informatics},
      volume = {P154},
      pages = {1241–1248},
      address = {Lübeck},
      organization = {GI}
    }
    
  • Kier, C., Meyer-Wiethe, K., Seidel, G. and Mertins, A.: Quality improvements for ultrasound-based cerebral perfusion analysis in Computer Assisted Radiology and Surgery -- CARS, 2009
    BibTeX
    @INPROCEEDINGS{Kier2009b,
      author = {Christian Kier and Karsten Meyer-Wiethe and Günter Seidel and Alfred
    	Mertins},
      title = {Quality improvements for ultrasound-based cerebral perfusion analysis},
      booktitle = {Computer Assisted Radiology and Surgery -- CARS},
      year = {2009}
    }
    
    
  • Kier, C., Meyer-Wiethe, K., Seidel, G. and Mertins, A.: Improved Modelling of Ultrasound Contrast Agent Diminution for Blood Perfusion Analysis in Medical Image Computing and Computer Aided Interventions -- MICCAI, 2009
    BibTeX
    @INPROCEEDINGS{Kier2009a,
      author = {Christian Kier and Karsten Meyer-Wiethe and Günter Seidel and Alfred
    	Mertins},
      title = {Improved Modelling of Ultrasound Contrast Agent Diminution for Blood
    	Perfusion Analysis},
      booktitle = {Medical Image Computing and Computer Aided Interventions -- MICCAI},
      year = {2009}
    }
    
    

2008

  • Kier, C., Seidel, G., Brüggemann, N., Hagenah, J., Klein, C., Aach, T. and Mertins, A.: Transcranial sonography as early indicator for genetic Parkinson’s disease in 4th European Congress for Medical and Biomedical Engineering, pp. 456--459, 2008
    BibTeX
    @INPROCEEDINGS{Kier2008,
      author = {C. Kier and G. Seidel and N. Br{\"u}ggemann and J. Hagenah and C. Klein
    	and T. Aach and A. Mertins},
      title = {Transcranial sonography as early indicator for genetic Parkinson’s
    	disease},
      booktitle = {4th European Congress for Medical and Biomedical Engineering},
      year = {2008},
      pages = {456--459},
      abstract = {Early diagnosis of Parkinson’s disease (PD) is of immense importance,
    	since clinical symptoms do not occur until substantial parts of the
    	brain stem have been irreparably damaged. Recent work suggests that
    	by means of transcranial sonography (TCS) it is possible to determine
    	the formation of monogenic forms of parkinsonism at a very early
    	state. In TCS images, the mesencephalon shows a distinct hyperechogenic
    	pattern in about 90% of patients with PD, despite its normal appearance
    	on CT and MRI scans. At present, this pattern is manually segmented
    	and the region size is used as an early PD indicator. In order to
    	remove investigator dependence inherent to manual segmentation, we
    	develop and validate semi-automatic features to serve as risk factors
    	for PD manifestation. We show in a clinical study that some of the
    	features correlate significantly with the presence of specific genetic
    	mutations causing PD.},
      file = {Kier2008.pdf:christian/Kier2008.pdf:PDF},
      keywords = {parkinson},
      owner = {kier},
      timestamp = {2009.01.22}
    }
  • Maciak, A., Seidel, G., Meyer-Wiethe, K., Kier, C. and Hofmann, .. U.: Bolus Harmonic Imaging zur automatischen Erkennung ischämiebedingter Perfusionsdefizite im Gehirn Ultraschall in der Medizin, in Automatic Detection of Perfusion Deficits with Bolus Harmonic Imaging, vol. 29, pp. --, 2008
    BibTeX Link
    @ARTICLE{Maciak2008,
      author = {Maciak, A. and Seidel, G. and Meyer-Wiethe, K. and Kier, C. and Hofmann,
    	U.G.},
      title = {Bolus Harmonic Imaging zur automatischen Erkennung ischämiebedingter
    	Perfusionsdefizite im Gehirn},
      journal = {Ultraschall in der Medizin},
      year = {2008},
      volume = {29},
      pages = {--},
      abstract = {Zusammenfassung
    	
    	
    	Ziel: Die Diagnose zerebrovaskulärer Erkrankungen stützt sich zunehmend
    	auf den Einsatz ultraschallbasierter Verfahren. Das kontrastmittelgestützte,
    	transkranielle Bolus Harmonic Imaging (BHI) hat hierbei einen hohen
    	Stellenwert. Die Auswertung der aufgezeichneten Bildsequenz erfolgt
    	durch geübte Ärzte jedoch manuell und ist somit zeitaufwendig. Das
    	Ziel der hier beschriebenen drei Verfahren ist die sichere, vollautomatische
    	Erkennung von Perfusionsdefekten des Gehirns. Material und Methoden:
    	Mit dem BHI werden Ultraschallbildsequenzen aufgezeichnet, die die
    	Kontrastmitteldynamik im Gehirn wiedergeben. Diese Bilder werden
    	mit drei verschiedenen Verfahren automatisch ausgewertet. Zum einen
    	wird ein regelbasiertes System beschrieben, welches aus den aufgezeichneten
    	Ultraschallbildern Parameterbilder extrahiert und diese mithilfe
    	von Expertenwissen nach perfundierten und minderperfundierten Gehirnarealen
    	klassifiziert. Zum zweiten erfolgt die Klassifikation der Gehirngebiete
    	unüberwacht mit dem K-Means-Verfahren. Hierzu wird jedes der Parameterbilder
    	als eine Dimension des zu klassifizierenden Merkmalsraums betrachtet,
    	sodass eine unüberwachte Segmentierung der minderperfundierten Gehirnbereiche
    	möglich ist. Drittens wird die gesamte Bildsequenz anhand der Kontrastmitteldynamik
    	pixelweise klassifiziert. Hierbei kann darauf verzichtet werden,
    	Parameterbilder extrahieren zu müssen. In allen drei Fällen ist es
    	im Anschluss notwendig, die beim HI auftretenden Streifenartefakte
    	automatisch zu erkennen. Abschließend wird ein Aussagenbild generiert,
    	in dem die gefundenen Minderperfusionen markiert sind. Ergebnisse:
    	Die drei Verfahren wurden auf einem 26 Patienten umfassenden Kollektiv
    	klinisch validiert. Hierbei hat sich herausgestellt, dass insbesondere
    	die Segmentierung anhand der Kontrastmitteldynamik dazu geeignet
    	ist, Minderperfusionen automatisch zu erkennen. Es konnte auf diesem
    	Patientenkollektiv eine Sensitivität von 100 % bei einer Spezifität
    	von 100 % erreicht werden. Schlussfolgerungen: Alle drei Verfahren
    	erscheinen geeignet, ischämische Gehirngebiete zu erkennen. Hierbei
    	liefert die Klassifikation von Gehirngebieten nach der Kontrastmitteldynamik
    	die besten Ergebnisse, da sie robust gegenüber Rauschen ist. Zudem
    	ist es das schnellste Verfahren, da die Extraktion von Parameterbildern
    	entfällt. Es ist notwendig, die Sensitivität und Spezifität auf einem
    	größeren Patientenkollektiv zu validieren. Eine sichere, vollautomatische
    	Erkennung von Perfusionsdefekten direkt am Patientenbett scheint
    	somit möglich zu sein.
    	
    	Abstract
    	
    	
    	Purpose: The diagnosis of ischemic stroke relies increasingly on the
    	usage of ultrasound-based methods. One of the recent methods is the
    	transcranial, contrast agent-based Bolus Harmonic Imaging (BHI) method.
    	The captured image sequence is manually examined by clinical experts
    	thus resulting in a time-consuming procedure. The purpose of this
    	study is to evaluate three different methods to analyze BHI image
    	sequences automatically for the detection of ischemic brain tissue.
    	Materials and Method: BHI captures an image sequence that provides
    	information on the dynamic behavior of the ultrasound contrast agents.
    	This image sequence is analyzed using three different procedures.
    	First a system relying on expert knowledge is used to determine perfusion
    	defects. This procedure requires parametric images, which are previously
    	extracted from the image sequence. The parameter images are then
    	categorized by an unsupervised classification method in well-perfused
    	and ischemic tissue by regarding the parametric images as features
    	describing the perfusion. Thirdly, the whole image sequence can be
    	interpreted as a pixel-by-pixel behavior out of contrast agents.
    	The dynamic curve of each pixel can be automatically classified as
    	perfused and ischemic tissue by the K-Means method without extracting
    	parametric images. In all three cases a closing step is necessary
    	for the accurate interpretation of the results. Transcranial ultrasound
    	imaging produces typical stripe artifacts that have to be detected
    	and eliminated. A result image is then created and provides a conclusion
    	about perfusion reduction in brain tissue. Results: All three methods
    	have been validated on the basis of 26 patients by clinical experts.
    	The segmentation on the contrast agent kinetics has proven to be
    	most effective. According to our patient database, it provides the
    	highest detection accuracy, resulting in a sensitivity of 100 % and
    	a specificity of 100 %. Conclusion: The presented methods seem to
    	be adequate for detecting ischemic brain tissue. The classification
    	of contrast agent kinetics provides the best results and has further
    	advantages. It is robust with respect to noise and the calculation
    	is fast because the extraction of parametric images is omitted. The
    	very high sensitivity and specificity must be validated in a larger
    	patient population. Reliable and automated detection of perfusion
    	defects at the bedside seems to be possible.},
      booktitle = {Automatic Detection of Perfusion Deficits with Bolus Harmonic Imaging},
      doi = {10.1055/s-2008-1027190},
      refid = {101055S20081027190}
    }
    

2007

  • Kier, C., Meyer-Wiethe, K., Seidel, G. and Aach, T.: Ultrasound Cerebral Perfusion Analysis Based on a Mathematical Model for Diminution Harmonic Imaging Methods of Information in Medicine, vol. 46, no. 3, pp. 308--13, 2007
    BibTeX Link
    @ARTICLE{Kier2007a,
      author = {C. Kier and K. Meyer-Wiethe and G. Seidel and T. Aach},
      title = {Ultrasound Cerebral Perfusion Analysis Based on a Mathematical Model
    	for Diminution Harmonic Imaging},
      journal = {Methods of Information in Medicine},
      year = {2007},
      volume = {46},
      pages = {308--13},
      number = {3},
      doi = {10.1160/ME9048},
      keywords = {perfuscope}
    }
    
  • Kier, C., Cyrus, C., Seidel, G., Hofmann, U. G. and Aach, T.: Segmenting the substantia nigra in ultrasound images for early diagnosis of Parkinson s disease International Journal of Computer Assisted Radiology and Surgery, vol. 2, no. S1, pp. S83-S85, June, 2007
    BibTeX Link
    @ARTICLE{Kier2007,
      author = {Christian Kier and Christina Cyrus and Günter Seidel and Ulrich G.
    	Hofmann and Til Aach},
      title = {Segmenting the substantia nigra in ultrasound images for early diagnosis
    	of Parkinson's disease},
      journal = {International Journal of Computer Assisted Radiology and Surgery},
      year = {2007},
      volume = {2},
      pages = {S83--S85},
      number = {S1},
      month = {June},
      doi = {10.1007/s11548-007-0086-4},
      keywords = {parkinson}
    }
  • Maciak, A., Kier, C., Seidel, G., Meyer-Wiethe, K., Hofmann, U. and Aach, T.: Robuste Ermittlung parametrischer Bilder für die Ultraschall-Perfusionsbildgebung basierend auf einem Modell der Boluskinetik von Kontrastmitteln Biomedizinische Technik. Ergänzungsband., vol. 52, pp. Session A2, Berlin, 2007
    BibTeX
    @ARTICLE{Maciak2007b,
      author = {Adam Maciak and Christian Kier and G{\"u}nter Seidel and Karsten Meyer-Wiethe
    	and Ulrich Hofmann and Til Aach},
      title = {Robuste Ermittlung parametrischer Bilder für die Ultraschall-Perfusionsbildgebung
    	basierend auf einem Modell der Boluskinetik von Kontrastmitteln},
      journal = {Biomedizinische Technik. Ergänzungsband.},
      year = {2007},
      volume = {52},
      pages = {Session A2},
      address = {Berlin},
      issn = {0939-4990},
      keywords = {perfuscope}
    }
  • Maciak, A., Kier, C., Seidel, G., Meyer-Wiethe, K. and Hofmann, U. G.: Detecting Stripe Artifacts in Ultrasound Images Journal of Digital Imaging, 2007
    BibTeX Link Link
    @ARTICLE{Maciak2007a,
      author = {A. Maciak and C. Kier and G. Seidel and K. Meyer-Wiethe and U. G.
    	Hofmann},
      title = {Detecting Stripe Artifacts in Ultrasound Images},
      journal = {Journal of Digital Imaging},
      year = {2007},
      doi = {10.1007/s10278-007-9049-0},
      url = {http://www.springerlink.com/content/rm058658xpv37ph2/?p=fbae785cac25420b93dd3c1a6b1428a9&pi=0}
    }
    
  • Maciak, A., Kier, C., G., S., Meyer-Wiethe, K. and Hofmann, .. G.: Automatische Erkennung von Ischämien mit Bolus Harmonic Imaging in Bildverarbeitung für die Medizin 2007, pp. 81-86, Springer-Verlag, München, 25-27 March, 2007
    BibTeX
    @INPROCEEDINGS{Maciak2007,
      author = {Maciak, A. and Kier, C. and Seidel G. and Meyer-Wiethe, K. and Hofmann,	U. G.},
      title = {{Automatische Erkennung von Isch{\"a}mien mit Bolus Harmonic Imaging}},
      booktitle = {Bildverarbeitung f{\"u}r die Medizin 2007},
      year = {2007},
      editor = {A. Horsch, T. M. Deserno, H. Handels, H.-P. Meinzer, T. Tolxdorf},
      pages = {81-86},
      address = {M{\"u}nchen},
      month = {25-27 March},
      publisher = {Springer-Verlag},
      isbn = {3540710905}
    }
    

2006

  • Kier, C., Meyer-Wiethe, K., Seidel, G. and Aach, T.: Ultraschall-Perfusionsbildgebung für die Schlaganfalldiagnostik auf Basis eines Modells für die Destruktionskinetik von Kontrastmittel in Bildverarbeitung für die Medizin 2006, pp. 41--45, Springer, Informatik Aktuell, Heidelberg, March, 2006
    BibTeX
    @Inproceedings{Kie06a,
    author              = { Christian Kier and Karsten Meyer-Wiethe and G{\"u}nter Seidel
                            and Til Aach },
    title               = { Ultraschall-Perfusionsbildgebung f{\"u}r die Schlaganfalldiagnostik
                            auf Basis eines Modells f{\"u}r die Destruktionskinetik
                            von Kontrastmittel },
    pages               = { 41--45 },
    month               = {March},
    year                = 2006,
    editor              = { H. Handels and J. Ehrhardt and A. Horsch and H.-P. Meinzer
                            and T. Tolxdoff },
    publisher           = {Springer},
    series              = { Informatik Aktuell },
    address             = {Heidelberg},
    booktitle           = { Bildverarbeitung f{\"u}r die Medizin 2006 }
    }
  • Kier, C. and Aach, T.: Predicting the benefit of sample size extension in multiclass k-NN classification in Pattern Recognition, 2006. ICPR 2006. 18th International Conference on, vol. 3, pp. 332--335, 20-24 Aug., 2006
    BibTeX Link
    @INPROCEEDINGS{Kier2006a,
      author = {Christian Kier and  Til Aach},
      title = {Predicting the benefit of sample size extension in multiclass k-NN
    	classification},
      booktitle = {Pattern Recognition, 2006. ICPR 2006. 18th International Conference
    	on},
      year = {2006},
      volume = {3},
      pages = {332--335},
      month = {20-24 Aug.},
      doi = {10.1109/ICPR.2006.942}
    }
    
  • Maciak, A., Kier, C., Seidel, G., Meyer-Wiethe, K. and Aach, T.: Parameterfreie Erkennung von Ischämien mit ultraschallbasiertem Harmonic Imaging in Proceedings BMT, pp. V76, ISSN 0939-4990, Zürich, September, 2006
    BibTeX
    @INPROCEEDINGS{Maciak2006,
      author = {Adam Maciak and Christian Kier and G{\"u}nter Seidel and Karsten Meyer-Wiethe and Til Aach},
      title = {Parameterfreie Erkennung von Isch{\"a}mien mit ultraschallbasiertem Harmonic Imaging},
      booktitle = {Proceedings BMT},
    series = {ISSN 0939-4990},
      year = {2006},
      pages = {V76},
      address = {Z{\"u}rich},
    month = {September},
      keywords = {perfuscope}
    }
    
  • Seidel, G., Cangür, H., Meyer-Wiethe, K., Renault, G., Herment, A., Schindler, A. and Kier, C.: On the ability of ultrasound parametric perfusion imaging to predict the area of infarction in acute ischemic stroke. Ultraschall Med, vol. 27, no. 6, pp. 543--548, Dec, 2006
    BibTeX Link Link
    @ARTICLE{Seidel2006,
      author = {G. Seidel and H. Cang{\"u}r and K. Meyer-Wiethe and G. Renault and A.
    	Herment and A. Schindler and C. Kier},
      title = {On the ability of ultrasound parametric perfusion imaging to predict
    	the area of infarction in acute ischemic stroke.},
      journal = {Ultraschall Med},
      year = {2006},
      volume = {27},
      pages = {543--548},
      number = {6},
      month = {Dec},
      abstract = {PURPOSE: Cerebral perfusion deficits in acute ischemic stroke can
    	be detected by means of transcranial harmonic imaging after ultrasound
    	contrast agent bolus injection. We evaluated five different parameters
    	of the bolus kinetics as parametric images and correlated areas of
    	disturbed perfusion with the area of definite infarction. MATERIALS
    	AND METHODS: Perfusion harmonic imaging after SonoVue bolus injection
    	(BHI) was used to investigate 22 patients suffering from acute internal
    	carotid artery infarction. For each subject, we calculated five different
    	images based on the following parameters from the time-intensity
    	curve in each pixel: pixelwise peak intensity (PPI), area under the
    	curve (AUC), positive gradient (PG), time to peak (TTP), and a three
    	factor image from the factor analysis of medical image sequences
    	(FAMIS). The findings in the diencephalic imaging plane were compared
    	with the definite area of infarction, as diagnosed by cranial CT.
    	RESULTS: In predicting the definite area of infarction in follow-up
    	CT, we found the following sensitivities and positive predictive
    	values (PPV): PPI (100 \%/95 \%), AUC (100 \%/90 \%), FAMIS (89 \%/89
    	\%), PG (84 \%/94 \%) and TTP (47 \%/100 \%). The areas of disturbed
    	perfusion in all five types of parametric images correlated significantly
    	with the area of infarction in CT. Images from the FAMIS algorithm
    	and PPI images showed the highest Spearman rank correlation with
    	the area of definite infarction as displayed in CT (both r = 0.76,
    	p < 0.001). Images from the other parameters correlated as follows:
    	PG: r = 0.62 (p = 0.003), AUC: r = 0.53 (p = 0.014), TTP: r = 0.50
    	(p = 0.021). CONCLUSION: BHI can detect disturbed perfusion in acute
    	hemispheric stroke. In their ability to predict the development of
    	an infarction, intensity-based parameters and FAMIS were determined
    	to have a high sensitivity, and TTP was found to have a high PPV
    	and specificity.},
      doi = {10.1055/s-2006-927023},
      pmid = {17146746},
      url = {http://dx.doi.org/10.1055/s-2006-927023}
    }
    

2005

  • Seidel, G., Cangör, H., Meyer-Wiethe, K., Renault, G., Herment, A., Schindler, A., Kier, C. and Aach, T.: Sonographische Darstellung der Hirnperfusion zur Prädiktion des Hirninfarkts bei Patienten mit akutem Schlaganfall 2005
    BibTeX
    @InProceedings{Seidel05,
    	title = {Sonographische Darstellung der Hirnperfusion zur Prädiktion des Hirninfarkts bei Patienten mit akutem Schlaganfall},
    	author = {G Seidel and H Cang{\"o}r and K Meyer-Wiethe and G Renault and A Herment and A Schindler and C Kier and T Aach},
    	year = {2005}
    }
  • Vollrath, A., Kier, C., Meyer-Wiethe, K., Seidel, G. and Aach, T.: Detecting Stripe Artefacts in Ultrasound Parametric Images Biomedizinische Technik, vol. 50, no. suppl. vol. 1, pp. 1235--1236, Fachverlag Schiele und Schön, Berlin, September, 2005
    BibTeX
    @Article{Vol05a,
    author              = { Antje Vollrath and Christian Kier and Karsten Meyer-Wiethe and G{\"u}nter Seidel and Til Aach },
    title               = { Detecting Stripe Artefacts in Ultrasound Parametric Images },
    journal             = { Biomedizinische Technik },
    volume              = 50,
    number              = { suppl. vol. 1 },
    pages               = { 1235--1236 },
    month               = {September},
    year                = 2005,
    publisher           = { Fachverlag Schiele und Sch{\"o}n },
    address             = {Berlin}
    }
  • Kier, C., Toth, D., Meyer-Wiethe, K., Schindler, A., Cangür, H., Seidel, G. and Aach, T.: Cerebral Perfusion Imaging with Bolus Harmonic Imaging in Ultrasonic Imaging and Signal Processing, vol. 5750, pp. 437-446, Proceedings of SPIE, San Diego, CA, February, 2005
    BibTeX
    @Inproceedings{Kie05a,
    author              = { Christian Kier and Daniel Toth and Karsten Meyer-Wiethe
                            and Angela Schindler and Hakan Cang{\"u}r and G{\"u}nter
                            Seidel and Til Aach },
    title               = { Cerebral Perfusion Imaging with Bolus Harmonic Imaging },
    volume              = {5750},
    pages               = { 437--446 },
    month               = {February},
    year                = {2005},
    editor              = { William F. Walker and Stanislav Y. Emelianov },
    series              = { Proceedings of SPIE },
    address             = { San Diego, CA },
    booktitle           = { Ultrasonic Imaging and Signal Processing },
    }
    

2004

  • Seidel, G., Kier, C., Meyer-Wiethe, K., Toth, D., Schindler, A. and Aach, T.: Sonografische Parameterbilder zur Darstellung der Hirnperfusion bei Patienten mit akutem Hirninfarkt 2004
    BibTeX
    @inproceedings{Seidel04,
    author          = {G{\"u}nter Seidel and Christian Kier and Karsten Meyer-Wiethe and Daniel Toth and Angela Schindler and Til Aach},
    title           = {Sonografische Parameterbilder zur Darstellung der Hirnperfusion bei Patienten mit akutem Hirninfarkt},
    year            = {2004}
    }