Journal Papers  
 
  1. E.M. Muller-Oehring, D. Kwon, B.J. Nagel, E.V. Sullivan, W. Chu, T. Rohlfing, D. Prouty, N. Nichols, J-B Poline, S.F Tapert, S.A Brown, K. Cummins, T. Brumback, I.M. Colrain, F.C. Baker, M.D De Bellis, J. Voyvodic, D.B. Clark, A. Pfefferbaum, K.M. Pohl. Influences of age, sex, and moderate alcohol drinking on the intrinsic functional architecture of adolescent brains, Cerebral Cortex, In Press.
  2. E.V. Sullivan, T. Brumback, S.F Tapert, D. Prouty, R. Fama, W. Thompson, S.A Brown, K. Cummins, I.M. Colrain, F.C. Baker, D.B. Clark, T. Chung, M.D De Bellis, S. Hooper, B.J. Nagel, W. Chu, D. Kwon, K.M. Pohl, A. Pfefferbaum. Effects of prior testing lasting a full year in NCANDA adolescents: Contributions from age, sex, socioeconomic status, ethnicity, site, family history of alcohol or drug abuse, and baseline performance, Developmental Cognitive Neuroscience, In Press.
  3. E.V. Sullivan, B. Lane, D. Kwon, M.J. Meloy, S.F Tapert, S.A Brown, I.M. Colrain, F.C. Baker, M.D De Bellis, D.B. Clark, B.J. Nagel, K.M. Pohl, A. Pfefferbaum. Structural brain anomalies in healthy adolescents in the NCANDA cohort: Relation to neuropsychological test performance, sex, and ethnicity, Brain Imaging and Behavior, In Press.
  4. Y. Zhang, D. Kwon, P.E. Esmaeili-Firidouni, A. Pfefferbaum, E.V. Sullivan, H. Javitz, V. Valcour, K.M. Pohl: Extracting Patterns of Morphometry Distinguishing HIV Associated Neurodegeneration from Mild Cognitive Impairment via Group Cardinality Constrained Classification, Human Brain Mapping, 37(12):4523-4538, 2016.
  5. Y. Zhang, D. Kwon, K.M. Pohl. Computing Group Cardinality Constraint Solutions for Logistic Regression Problems, Medical Image Analysis, 35, pp.58-69, 2017.
  6. A. Pfefferbaum, T. Rohlfing, K. M. Pohl, B. Lane, W. Chu, D. Kwon, S.A. Brown, S.F. Tapert, K. Cummins, W.K. Thompson, T. Brumback, M.J. Meloy, T.L. Jernigan, A. Dale, I.M. Colrain, F.C. Baker, D. Prouty, M.D. De Bellis, J.T. Voyvodic, D.B. Clark, B. Luna, T. Chung, B. Nagel, E.V. Sullivan. Adolescent development of cortical and white matter structure in the NCANDA sample: Role of sex, ethnicity, puberty, and alcohol drinking, Cerebral Cortex, In Press
  7. K.M. Pohl, E.V. Sullivan, T. Rohlfing, W. Chu, D. Kwon, B.N. Nichols, Y. Zhang, S.A Brown, S.F Tapert, K. Cummins, W.K. Thompson, T. Brumback, I.M. Colrain, F.C. Baker, D. Prouty, M.D De Bellis, J.T Voyvodic, D.B. Clark, C. Schrida, B.J. Nagel, A. Pfefferbaum. Harmonizing DTI Measurements across Scanners to Examine the Development of White Matter Microstructure in 803 Adolescents of the NCANDA Study, NeuroImage, 130, 194-213, 2016
  8. E.V. Sullivan, S.F. Tapert, R. Fama, T. Brumback, D. Prouty, S.A. Brown, K. Cummins, W.K. Thompson, I.M. Colrain, F.C. Baker, M.D. De Bellis, S.R. Hooper, D.B. Clark, T. Chung, B. Nagel, B.N. Nichols, T. Rohlfing, W. Chu, K.M. Pohl, A. Pfefferbaum: Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction, Neuropsychology, , 30(4):449-473, 2016
  9. B.N. Nichols, K.M. Pohl. Neuroinformatics Software Applications Supporting Electronic Data Capture, Management, and Sharing for the Neuroimaging Community, Neuropsychology Review, 25(3):356-68, 2015
  10. Brown, S.A., Brumback, T., Tomlinson, K., Cummins, K., Thompson, W.K., Nagel, B.J., De Bellis, M.D., Hooper, S.R., Clark, D.B., Chung, T., Hasler, B.P., Colrain, I.M., Baker, F.B., Prouty, D., Pfefferbaum, A., Sullivan, E.V., Pohl, K.M., Rohlfing, T., Nichols, B.N., Chu, W., Tapert, S.F. The National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA): A multi-site study of adolescent development and substance use, Journal of Studies on Alcohol and Drugs, 76(6), 895-908, 2015
  11. A.  Pfefferbaum, M.J.  Rosenbloom, W.  Chu, S.A.  Sassoon, T.  Rohlfing, K.M.  Pohl, N.M.  Zahr, E.V.  Sullivan: White Matter Microstructural Recovery with Abstinence and Decline with Relapse in Alcoholism: A Controlled Longitudinal DTI Study, The Lancet Psychiatry, 1(3), pp 202 - 212, 2014.
  12. D.H.  Ye, B.  Desjardins, J. Hamm, H.  Litt, K.M. Pohl. Regional Manifold Learning for Disease Classification, IEEE Transactions on Medical Imaging, 33(6), pp 1236 - 1247, 2014.
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  13. D. Kwon, M. Niethammer, H. Akbari, M. Billelo, C. Davatzikos, K.M. Pohl. PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration, IEEE Transactions on Medical Imaging, 33(3), pp. 651 - 667, 2014.
    [ PDF ]
  14. E. Konukoglu, B. Glocker, A. Criminisi, K.M. Pohl. WESD - Weighted Spectral Distance for Measuring Shape Dissimilarity, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2284-2297, 2013.
    [ PDF ]
  15. E. Konukoglu, B. Glocker, D.H. Ye, A. Criminisi, K.M. Pohl. Discriminative Segmentation-based Evaluation through Shape Dissimilarity, IEEE Transactions on Medical Imaging, 31(12), pp 2278-89, 2012.
    [ PDF]
  16. A. Gooya, K.M. Pohl, M. Billelo, L. Cirillo, G. Biros, E.R. Melhem, C. Davatzikos. GLISTR: Glioma Image Segmentation and Registration, IEEE Transaction on Medical Imaging, 31(10), pp 1941-54, 2012.
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  17. K.M Pohl, E. Konukoglu, S. Novellas, N. Ayache, A. Fedorov, I.-F. Talos, A. Golby, W.M. Wells, R. Kikinis, P.M. Black. A New Metric for Detecting Change in Slowly Evolving Brain Tumors: Validation in Meningioma Patients,Neurosurgery, Mar;68(1 Suppl Operative):225-33, 2011.
    [ PDF]
  18. A. Fedorov, X. Li, K.M. Pohl, S. Bouix, M. Styner, M. Addicott, C. Wyatt, J.B. Daunais, W.M. Wells, R. Kikinis. Atlas-guided Segmentation of Vervet Monkey Brain MRI, Special Issue on Neuroimaging of non-human Primates in Open Neuroimage Journal, 5(Suppl 2-M7), pp.186-197, 2011.
    [ PDF]
  19. K.M. Pohl, J. Fisher, S. Bouix, M.E. Shenton, R.W. McCarley, W.E.L. Grimson, R. Kikinis, and W.M. Wells. Using the logarithm of odds to define a vector space on probabilistic atlases. Medical Image Analysis, 11(6), pp. 465-477, 2007.
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  20. K.M. Pohl, S. Bouix, M. Nakamura, T. Rohlfing, R.W. McCarley, R. Kikinis, W.E.L. Grimson, M.E. Shenton, and W.M. Wells. A hierarchical algorithm for MR brain image parcellation. IEEE Transactions on Medical Imaging, 26(9),pp 1201-1212, 2007.
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  21. M. Nakamura, D.F. Salisbury, Y. Hirayasu, S. Bouix, K.M. Pohl, T. Yoshida, M.S. Koo, M.E. Shenton, and R.W. McCarley. Neocortical gray matter volume in first episode schizophrenia and first episode affective psychosis: a cross-sectional and longitudinal MRI study. Biological Psychiatry, 62(7), pp. 773-83, 2007.
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  22. K. M. Pohl, J. Fisher, W.E.L. Grimson, R. Kikinis, and W.M. Wells. A Bayesian model for joint segmentation and registration. NeuroImage, 31(1), pp. 228-239, 2006
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  23. M.-S. Koo, C. C. Dickey, M. E. Shenton, N. Y. Ji, S. Bouix, K. M. Pohl, J. J. Levitt, M. Nakamura, and R. W. McCarley. Smaller neocortical gray matter and larger sulcal CSF volumes in neuroleptic-naive females with schizotypal personality disorder. Archives of General Psychiatry, 63, pp. 1090-1100, 2006.
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  Peer Reviewed Papers  
 
  1. Y.. Zhang, S.. Park, K.M.. Pohl: Joint Data Harmonization and Group Cardinality Constrained Classification, Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag, Lecture Notes in Computer Science, 9900, pp. 282–290, 2016.
  2. Y. Zhang,K.M. Pohl:Solving Logistic Regression with Group Cardinality Constraints for Time Series Analysis, MICCAI 2015: Eighteenth International Conference Medical Image Computing and Computer-Assisted Intervention, Munich, Germany, 2015. [PDF]
  3. D.H. Ye, B. Desjardins, V. Ferrari, D. Metaxas, K.M. Pohl: Auto-Encoding of Discriminating Morphometry from Cardiac MRI, accepted to ISBI 2014: IEEE International Symposium on Biomedical Imaging, Beijing, China
    [ PDF]
  4. D.H. Ye, J. Hamm, B.  Desjardins , K.M. Pohl: FLOOR: Fusing Locally Optimal Registrations, MICCAI 2013: Sixteenth International Conference Medical Image Computing and Computer-Assisted Intervention, Nagoya, Japan, Springer, LNCS 8151, pp 195-202, 2013.
    [PDF]
  5. M.G. Uzunbas, C. Chen, S. Zhang, K.M. Pohl, K. Li, D. Metaxas: Collaborative Multi Organ Segmentation by Integrating Deformable and Graphical Models, accepted to MICCAI 2013: Sixteenth International Conference Medical Image Computing and Computer-Assisted Intervention, Nagoya, Japan, LNCS 8150, pp 157-164, 2013.
  6. B. Tunc, A. Smith, D. Wassermann, X. Pennec, W.M. Wells, R. Verma, K.M. Pohl: Multinomial Probabilistic Fiber Representation for Connectivity Driven Clustering, IPMI 2013: The 23rd biennial International Conference on Information Processing in Medical Imaging, Asilomar, California, Springer, LNCS 7917, pp 730–41, 2013.
    [ PDF]
  7. E. Bernardis, K.M. Pohl, C. Davatzikos: Extracting Evolving Pathologies via Spectral Clustering, accepted to IPMI 2013: The 23rd biennial International Conference on Information Processing in Medical Imaging, Asilomar, California, Springer-Verlag, LNCS 7511, pp. 49-56, 2012.
    [ PDF]
  8. D.H. Ye, J. Hamm, C. Davatzikos, K.M. Pohl: Regional Manifold Learning for Deformable Registration of Brain MR Images, In Proc MICCAI 2012: Fifteenth International Conference Medical Image Computing and Computer-Assisted Intervention, Nice, France, Springer-Verlag, LNCS 7512, pp. 131-138, 2012.
    [ PDF]
  9. E. Bernardis, E. Konukoglu, Y. Ou, D. Metaxas, B. Desjardins, KM Pohl: Temporal Shape Analysis via the Spectral Signature, In Proc MICCAI 2012: Fifteenth International Conference Medical Image Computing and Computer-Assisted Intervention, Nice, France, LNCS 7511, pp. 49-56, 2012.
    [ PDF]
  10. Y. Ou, D.H. Ye, K.M. Pohl, C. Davatzikos: Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration, In Proc WBIR 2012: Fifth Workshop on Biomedical Image Registration, Nashville, TN, Springer, Lecture Notes in Computer Science Volume, 7359, pp 209-219, 2012
  11. D.H. Ye, J. Hamm, K.M. Pohl: Combining Regional Metrics for Disease-Related Brain Population Analysis, In Proc. ISBI 2012: International Symposium on Biomedical Imaging, Barcelona, Spain, 2012.
    [ PDF]
  12. J. Jayender, K.G. Vosburgh, E. Gombos, A. Ashraf, D. Kontos, S.C. Gavenonis, F.A. Jolesz, K.M. Pohl: Automatic Segmentation of Breast Carcinomas from DCE-MRI Using a Statistical Learning Algorithm, In Proc. ISBI 2012: International Symposium on Biomedical Imaging, Barcelona, Spain, 2012.
  13. D. Kwon, D. Yun, K.M. Pohl, C. Davatzikos, S.U. Lee: Nonrigid Volume Registration Using a Second-Order MRF Model, In Proc. ISBI 2012: International Symposium on Biomedical Imaging, Barcelona, Spain, 2012.
  14. J. Eckl, V. Daum, J. Hornegger, K.M Pohl: Guiding Non-Rigid Registration via Landmarks and Learning, In Proc. ISBI 2012: International Symposium on Biomedical Imaging, Barcelona, Spain, 2012.
  15. M.G. Uzunbas, S. Zhang, K.M. Pohl, D. Metaxas, L. Axel: Segmentation of Myocardium Using Deformable Regions and Graph Cuts, In Proc. ISBI 2012: International Symposium on Biomedical Imaging, Barcelona, Spain, 2012.
  16. A. Gooya, K.M. Pohl, M.l Bilello, G. Biros, C. Davatzikos: Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model, In Proc. MICCAI 2011: Fourteenth International Conference Medical Image Computing and Computer-Assisted Intervention,Toronto, Canada, 2011
    [ PDF]
  17. B. Gaonkar, KM Pohl, C. Davatzikos: Pattern Based Morphometry, In Proc. MICCAI 2011: Fourteenth International Conference Medical Image Computing and Computer-Assisted Intervention,Toronto, Canada, 2011
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  18. D.H. Ye, H. Litt, C. Davatzikos, K.M. Pohl, Morphological Classification: Application to cardiac MRI of Tetralogy of Fallot, in Proc. of the Sixth International Conference on Functional Imaging and Modeling of the Heart, 2011.
    [ PDF]
  19. B. Gaonkar, G. Erus, K. M. Pohl, M. Tanwar, S. Margiewicz, R. N. Bryan, C. Davatzikos, Automated Segmentation of Cortical Necrosis Using a Wavelet Based Abnormality Detection System, in Proc. of the eighth IEEE International Symposium on Biomedical Imaging, 2011.
    [ PDF]
  20. N. Batmanghelich, D.H. Ye, K.M. Pohl, B. Taskar, C. Davatzikos, Disease Classification And Predication via Semi-Supervised Dimensionality Reduction, in Proc. the eighth IEEE International Symposium on Biomedical Imaging, 2011.
    [ PDF]
  21. D.H. Ye, K.M. Pohl, C. Davatzikos, Prediction of MCI to AD conversion via structural MRI using manifold learning and semi-supervised pattern classification, in Proc of IEEE International Workshop on Pattern Recognition in Neuroimaging, 2011.
  22. K. Chen, Y. Zhang, K.M. Pohl, T. Syeda-Mahmood, Z. Song, S.T.C Wong. Coronary Artery Segmentation Using Geometric Moments based Tracking and Snake-Driven Refinement, In Proc. EMBC 2010: 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina, 2010.
  23. Dong Hye Ye, Kilian M. Pohl, Harold Litt, and Christos Davatzikos. Groupwise Morphometric Analysis Based on High Dimensional Clustering, In Proc. MMBIA 2010: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis at CVPR 2010: IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010.
  24. T. Syeda-Mahmood, P. Turaga, D. Beymer, F. Wang, A. Amir, H. Greenspan, K.M. Pohl. Shape-based Similarity Retrieval of Doppler Images for Clinical Decision Support, In Proc. CVPR 2010: IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010
  25. A. Amir, D. Beymer, J. Grace, H. Greenspan, D. Gruhl, A. Hobbs, K.M. Pohl, T. Syeda-Mahmood, J. Terdiman, F. Wang. AALIM: A Cardiac Clinical Decision Support System Powered By Advanced Multi-modal Analytics, in Proc. MedInfo 2010: 13th International Congress on Medical Informatics, Cape Town, South Africa, 2010.
  26. K.M. Pohl and M. R. Sabuncu. A Unified Framework for MR Based Disease Classification. In Information Processing in Medical Imaging, vol. 5636 of Lecture Notes in Computer Science, pages 300-313. Springer-Verlag, 2009.
    [ PDF]
  27. E. Konukoglu, W. M. Wells, S. Novellas, N. Ayache, R. Kikinis, P. M. Black, and K.M. Pohl. Monitoring slowly evolving tumors. In ISBI 2008: The Fifth IEEE International Symposium on Biomedical Imaging, pages 812 -815, 2008.
    [PDF]
  28. T. Rehman, E. Haber, K.M. Pohl, S. Haker, M. Halle, F. Talos, L. Wald, R. Kikinis, A. Tannenbaum. Multimodal Registration of White Matter Brain Data via Optimal Mass Transport. In Computational Biomechanics for Medicine III Workshop at MICCAI 2008: Eleventh International Conference on Medical Image Computing and Computer-Assisted Intervention, 27 - 36, New York, USA, 2008.
    [PDF]
  29. K.G. Vosburgh, J. Stoll, V. Noble, K.M. Pohl, R.S.J. Estepar, B. Takacs. Image Registration Assists Novice Operators in Ultrasound Assessment of Abdominal Trauma. In Proc. MMVR16: Medicine Meets Virtual Reality 16, Studies in Health Technology and Informatics, vol. 132, pp. 532 -537, IOS Press, 2008.
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  30. K.M. Pohl, R. Kikinis, and W.M. Wells. Active mean fields: Solving the mean field approximation in the level set framework. In Information Processing in Medical Imaging, vol. 4584 of Lecture Notes in Computer Science, pages 26-37. Springer-Verlag, 2007.
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  31. L. Zöllei, M. Shenton, W.M. Wells III, K.M. Pohl. The Impact of Atlas Formation Methods on Atlas-Guided Brain Segmentation, Statistical Registration. In Pair-wise and Group-wise Alignment and Atlas Formation Workshop at MICCAI 2007: Tenth International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 39 - 46, Brisbane, Australia, 2007.
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  32. K.M. Pohl, J. Fisher, M. Shenton, R. W. McCarley, W.E.L. Grimson, R. Kikinis, and W.M. Wells. Logarithm odds maps for shape representation. In Proc. MICCAI 2006: Ninth International Conference Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag, LNCS 4191, pp. 955-963, 2006.
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  33. K.M. Pohl, J. Fisher, R. Kikinis, W.E.L. Grimson, and W.M. Wells, “Shape Based Segmentation of Anatomical Structures in Magnetic Resonance Images, ” In Proc. ICCV 2005: Computer Vision for Biomedical Image Applications: Current Techniques and Future Trend, An International Conference on Computer Vision Workshop, Beijing, China, Springer-Verlag, LNCS 3765, pp. 489-498, 2005
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  34. K.M. Pohl, J. Fisher, J.J. Levitt, M.E. Shenton, R. Kikinis, W.E.L. Grimson, and W.M. Wells, “ A Unifying Approach to Registration, Segmentation, and Intensity Correction, ” In Proc. MICCAI 2005: Eighth International Conference on Medical Image Computing and Computer Assisted Intervention, Palm Springs, CA, USA, Springer-Verlag, Part I, vol. 3749 of Lecture Notes in Computer Science, pp. 310-318, 2005
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  35. K.M. Pohl, S. Bouix, M.E. Shenton, W.E.L. Grimson, R. Kikinis,“ Automatic Segmentation Using Non-Rigid Registration ” In short communications of MICCAI 2005: Eighth International Conference on Medical Image Computing and Computer Assisted Intervention, Palm Springs, CA, USA, 2005
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  36. K.M. Pohl, S.K. Warfield, R. Kikinis, W.E. L. Grimson, W.M. Wells,“ Coupling Statistical Segmentation and PCA Shape Modeling,” In Proc. MICCAI 2004: Seventh International Conference on Medical Image Computing and Computer Assisted Intervention, Rennes / St-Malo, France, Springer-Verlag, vol. 3216 of Lecture Notes in Computer Science, pp. 151-159, 2004
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  37. K.M. Pohl , S. Bouix, R. Kikinis, W.E.L. Grimson, “ Anatomical Guided Segmentation with Non-Stationary Tissue Class Distributions in an Expectation-Maximization Framework, ” In Proc. ISBI 2004: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, pp. 81-84, 2004
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  38. K.M Pohl, W.M. Wells, A. Guimond, K. Kasai, M.E. Shenton, R. Kikinis, W.E.L. Grimson and S.K. Warfield, “ Incorporating Non-Rigid Registration into Expectation Maximization Algorithm to Segment MR Images,” In Proc. MICCAI 2002: Fifth International Conference on Medical Image Computing and Computer Assisted Intervention, Tokyo, Japan, Springer-Verlag, Part I, vol. 2488 of Lecture Notes in Computer Science, pp. 564-572, 2002
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  39. O. Rogalla, K.M. Pohl, and R. Dillmann, “ A general approach for modeling robots, Intelligent Robots and Systems, ” In Proc. IROS 2000: IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, vol. 3, pp. 1963 - 1968, 2000
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  Book Chapters  
 
  1. K.M. Pohl, E. Konukoglu, A.J. Golby, R. Kikinis, “ Automatic Tumor Growth Detection, ” In: M.N. Pamir, R.M. Black, R. Fahlbusch: Meningiomas: A Comprehensive Text, Philadelphia, Saunders, pp. 2671 - 271, 2010
  Theses  
 
  1. K.M. Pohl,“ Prior Information for Brain Parcellation,”PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, 2005
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  2. K.M. Pohl,“ Modellierung von Manipulationssystemen,” Master Thesis, Institut fuer Prozessrechentechnik, Automation und Robotik, Univerität Karlsruhe (TH), August 1998
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  Other Publications  
 
  1. K.M. Pohl, E. Konukoglu, A.J. Golby, P.M. Black, R. Kikinis. A Tool for Measuring Tumor Growth from Medical Images, RSNA 08: Radiology Society of North America Scientific Assembly and Annual Meeting, 2008.
  2. K.M. Pohl, J. Fisher, W.E.L. Grimson, W.M. Wells,“ An Expectation Maximization Approach for Integrated Registration, Segmentation, and Intensity Correction,” CSAIL Publications - Artificial Intelligence Series Publications, AIM-2005-010, pp. 1-13, 2005
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  3. K.M. Pohl, S. Timoner , R. Kikinis, W.E.L. Grimson, “ Modeling Shape in a Self-Adoptive Segmentation Algorithm,” HBM 2004: Tenth Annual Meeting of the Organization for Human Brain Mapping, Poster WE 281, 2004
    [PDF]
  4. Y. Wu, K.M. Pohl, S.K. Warfield, C.R.G. Guttmann,“Automated Segmentation of Cerebral Ventricular Compartments, ” In Proc. ISMRM 2003: International Society for Magnetic Resonance in Medicine Eleventh Scientific Meeting and Exhibition, Toronto, Ontaril, Canada, Program No. 906
    [PDF]