Dženan Zukić, Ph.D.

Staff R&D Engineer

Medical Computing

Kitware North Carolina
Carrboro, NC

Ph.D. in Computer Graphics
University of Siegen

Dipl.-Ing.
University of Sarajevo

Dzenan Zukic

Dženan Zukić, Ph.D., pronounced Jenan (IPA: ʤɛnan zukiʨ), is a staff R&D engineer on Kitware’s Medical Computing Team located in Carrboro, North Carolina. He is involved in many diverse medical image analysis projects, including image-based guidance of biopsy needles, shape analysis of baby craniums from CT scans, quantitative PET/CT imaging, pre-clinical ultrasound imaging, μCT image analysis, and medical image quality assessment. Some of these projects are integrated into software for medical devices or robotic companies, which are protected by non-disclosure agreements. He also works with many collaborators to help advance this field of science, contributing back to the open source community whenever he can.

In addition to these projects, Dženan helps maintain Kitware’s open source Insight Toolkit (ITK) and occasionally writes specialized modules for 3D Slicer. He has also contributed to ITK-SNAP, an open source 3D image viewer and segmentation tool.  

Prior to joining Kitware, Dženan was a research assistant at the University of Siegen in Germany. He also worked at BSTelecom in Sarajevo, Bosnia-Herzegovina.

Dženan received his Ph.D. in computer graphics from the University of Siegen in 2014. His research involved brain tumor segmentation and focused on the segmentation of vertebral bodies and the diagnosis of certain diseases from magnetic resonance images. In 2007, he received his master’s degree (Dipl.-Ing.) in Computer Science from the University of Sarajevo.

Awards

  • Golden Ring presented by the Electrical Engineering Faculty of the University of Sarajevo, 2007

  • Valedictorian of Druga Gimnazija Sarajevo, 2002

Publications

  1. D. Zukić, J. Cox, L. Kovach, J. Cole, J. Marron, T. Birdsong, and M. McCormick, "Bone Morphometry of Atlas-Segmented Mouse Femurs and Tibias," in 23rd International Workshop on Quantitative Musculoskeletal Imaging, 2022.
  2. T. Birdsong, B. Paniagua, J. Cole, J. Cox, S. Marron, D. Zukić, J. Vicory, and M. McCormick, "Femur Atlas Generation and Shape Analysis with Deformable Surface Registration," in 23rd International Workshop on Quantitative Musculoskeletal Imaging, 2022.
  3. D. Zukić, A. Haley, C. Lisle, J. Klo, K. Pohl, H. Johnson, and A. Chaudhary, "Medical Image Quality Assurance using Deep Learning," in Medical Imaging with Deep Learning, 2022. [URL]
  4. T. Czernuszewicz, A. Aji, C. Moore, S. Montgomery, B. Velasco, G. Torres, K. Anand, K. Johnson, A. Deal, D. Zukić, M. McCormick, B. Schnabl, C. Gallippi, P. Dayton, and R. Gessner, "Development of a Robotic Shear Wave Elastography System for Noninvasive Staging of Liver Disease in Murine Models," Hepatology Communications, pp. hep4.1912, Feb. 2022. [URL]
  5. D. Zukić, M. Jackson, D. Dimiduk, S. Donegan, M. Groeber, and M. McCormick, "ITKMontage: A Software Module for Image Stitching," Integrating Materials and Manufacturing Innovation, Mar. 2021. [URL]
  6. J. Vicory, D. Allemang, D. Zukic, J. Prothero, M. McCormick, and B. Paniagua, "An open-source solution for shape modeling of objects of challenging topologies," in Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2021. [URL]
  7. A. Butskova, R. Juhl, D. Zukić, A. Chaudhary, K. Pohl, and Q. Zhao, "Adversarial Bayesian Optimization for Quantifying Motion Artifact Within MRI," in Predictive Intelligence in Medicine. Springer International Publishing, 2021, pp. 83-92. [URL]
  8. D. Zukić and M. McCormick, "Web-based Registration Tools Based on ITKElastix," in One-page abstracts proceedings, 2020.
  9. R. Grothausmann, D. Zukić, M. McCormick, C. Mühlfeld, and L. Knudsen, "Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series," in Biomedical Image Registration. Springer International Publishing, 2020, pp. 23-33. [URL]
  10. P. Yushkevich, A. Pashchinskiy, I. Oguz, S. Mohan, J. Schmitt, J. Stein, D. Zukić, J. Vicory, M. McCormick, N. Yushkevich, N. Schwartz, Y. Gao, and G. Gerig, "User-Guided Segmentation of Multi-modality Medical Imaging Datasets with ITK-SNAP," Neuroinformatics, vol. 17, no. 1, pp. 83-102, Jan. 2019. [URL]
  11. R. Zhang, D. Zukić, D. Byrd, A. Enquobahrie, A. Alessio, K. Cleary, F. Banovac, and P. Kinahan, "PET/CT-guided biopsy with respiratory motion correction," International Journal of Computer Assisted Radiology and Surgery, vol. 14, no. 12, pp. 2187-2198, Dec. 2019. [URL]
  12. T. Czernuszewicz, V. Papadopoulou, J. Rojas, R. Rajamahendiran, J. Perdomo, J. Butler, M. Herlacher, G. O'Connell, D. Zukić, S. Aylward, P. Dayton, and R. Gessner, "A preclinical ultrasound platform for widefield 3D imaging of rodent tumors," in American Association for Cancer Research Annual Meeting, 2019.
  13. D. Zukić, D. Byrd, P. Kinahan, and A. Enquobahrie, "Calibration Software for Quantitative PET/CT Imaging Using Pocket Phantoms," Tomography: A Journal for Imaging Research, vol. 4, no. 3, pp. 148-158, Sep. 2018. [URL]
  14. T. Czernuszewicz, V. Papadopoulou, J. Rojas, R. Rajamahendiran, J. Perdomo, J. Butler, M. Harlacher, G. O’Connell, D. Zukić, S. Aylward, P. Dayton, and R. Gessner, "A new preclinical ultrasound platform for widefield 3D imaging of rodents," Review of Scientific Instruments, vol. 89, no. 7, pp. 075107, 2018. [URL]
  15. A. Porras, D. Zukić, A. Enquobahrie, R. Keating, G. Rogers, and M. Linguraru, "Personalized Optimal Planning of Fronto-Orbital Advancement Surgery for the Correction of Metopic Craniosynostosis from CT," in American Cleft Palate-Craniofacial Association's Annual Meeting, 2017.
  16. R. Zhang, D. Zukić, D. Byrd, A. Enquobahrie, A. Alessio, K. Cleary, and P. Kinahan, "A deformable registration workflow for motion correction in PET-CT guided biopsy," in Society of Nuclear Medicine and Molecular Imaging Annual Meeting, 2017.
  17. A. Porras, D. Zukić, A. Equobahrie, G. Rogers, and M. Linguraru, "Personalized Optimal Planning for the Surgical Correction of Metopic Craniosynostosis," in MICCAI Workshop on Clinical Image-based Procedures, 2016.
  18. D. Zukić, Z. Mullen, D. Byrd, P. Kinahan, and A. Enquobahrie, "A web-based platform for a high throughput calibration of PET scans," in Proceedings of the International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2016. [URL]
  19. D. Zukić, M. McCormick, G. Gerig, and P. Yushkevich, "RLEImage: run-length encoded memory compression scheme for an itk::Image," The Insight Journal, 2016. [URL]
  20. D. Zukić, J. Vicory, M. McCormick, L. Wisse, G. Gerig, P. Yushkevich, and S. Aylward, "nD morphological contour interpolation," The Insight Journal, 2016. [URL]
  21. B. Wood, D. Zukić, J. Qi, C. Meyer, R. Ortiz, C. Mendoza, A. Enquobahrie, M. Linguraru, and G. Rogers, "Evaluation of Fronto-Orbital Advancement for Coronal Synostosis using a 3D Statistical Shape Model," in Proceedings of the Congress of International Society of Craniofacial Surgery, 2015.
  22. B. Paniagua, D. Zukić, R. Ortiz, S. Aylward, B. Golden, T. Nguyen, and A. Enquobahrie, "Ultrasound-Guided Navigation System for Orthognathic Surgery," in MICCAI Workshop on Augmented Environments for Computer-Assisted Interventions, 2015. [URL]
  23. J. Qi, D. Zukić, B. Wood, G. Rogers, C. Meyer, R. Ortiz, C. Mendoza, A. Enquobahrie, and M. Linguraru, "Postoperative Evaluation of Craniosynostosis based on 3D Statistical Shape Model," in Proceedings of the International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2015.
  24. D. Zukić, J. Finet, E. Wilson, F. Banovac, G. Esposito, K. Cleary, and A. Enquobahrie, "SlicerPET: A workflow based software module for PET/CT guided needle biopsy," in Proceedings of the International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2015. [URL]
  25. R. Ortiz, D. Zukić, J. Qi, B. Wood, G. Rogers, A. Enquobahrie, and M. Linguraru, "Stress Analysis Of Cranial Bones For Craniosynostosis Surgical Correction," in Proceedings of the International Congress and Exhibition on Computer Assisted Radiology and Surgery, 2015.
  26. D. Zukić, "An Efficient Inflation Method for Segmentation of Medical 3D Images," Ph.D. dissertation, University of Siegen, 2015. [URL]
  27. D. Zukić, A. Vlasák, J. Egger, D. Hořínek, C. Nimsky, and A. Kolb, "Robust Detection and Segmentation for Diagnosis of Vertebral Diseases using Routine MR Images," Computer Graphics Forum, vol. 33, no. 6, pp. 190-204, 2014. [URL]
  28. J. Egger, D. Zukić, B. Freisleben, A. Kolb, and C. Nimsky, "Segmentation of Pituitary Adenoma: Graph-based vs. Balloon Inflation," Computer Methods and Programs in Biomedicine, vol. 110, no. 3, pp. 268-278, Jun. 2013. [URL]
  29. D. Zukić, A. Vlasák, T. Dukatz, J. Egger, D. Hořínek, C. Nimsky, and A. Kolb, "Segmentation of Vertebral Bodies in MR Images," in Vision, Modeling and Visualization, 2012. [URL]
  30. J. Egger, T. Kapur, T. Dukatz, M. Kolodziej, D. Zukić, B. Freisleben, and C. Nimsky, "Square-Cut: A Segmentation Algorithm on the Basis of a Rectangle Shape," PLoS ONE, vol. 7, no. 2, pp. e31064, 2012. [URL]
  31. D. Zukić, J. Egger, M. Bauer, D. Kuhnt, B. Carl, B. Freisleben, A. Kolb, and C. Nimsky, "Preoperative Volume Determination for Pituitary Adenoma," in SPIE Medical Imaging, 2011. [URL]
  32. J. Egger, D. Zukić, M. Bauer, D. Kuhnt, B. Carl, B. Freisleben, A. Kolb, and C. Nimsky, "A Comparison of Two Human Brain Tumor Segmentation Methods for MRI Data," in Russian-Bavarian Conference on Bio-Medical Engineering, 2010. [URL]
  33. D. Zukić, J. Egger, M. Bauer, D. Kuhnt, B. Carl, B. Freisleben, A. Kolb, and C. Nimsky, "Glioblastoma Multiforme Segmentation in MRI Data with a Balloon Inflation Approach," in Russian-Bavarian Conference on Bio-Medical Engineering, 2010. [URL]
  34. D. Zukić, C. Rezk-Salama, and A. Kolb, "A Neural Network Classifier of Volume Datasets," in International Conference on Computer Graphics and Artificial Intelligence, 2009. [URL]
  35. D. Zukić, C. Rezk-Salama, and A. Kolb, "Classifying Volume Datasets Based on Intensities and Geometric Features," in Intelligent Computer Graphics. Springer, 2009, pp. 63-85. [URL]
  36. D. Zukić, A. Elsner, Z. Avdagić, and G. Domik, "Neural networks in 3D medical scan visualization," in International Conference on Computer Graphics and Artificial Intelligence, 2008. [URL]
  37. D. Zukić, "Neuronske mreže u vizuelizaciji CT snimaka," Elektrotehnički Fakultet, Univerzitet u Sarajevu, 2007. [URL]
  38. A. Elsner, D. Zukić, G. Domik, Z. Avdagić, W. Schäfer, E. Fricke, and D. Bošković, "Semiautomatic Cardiac CT Scan Classification with a Semantic User Interface," University of Paderborn, Dec. 2007.

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