Dženan Zukić

Dženan Zukić

Senior R&D Engineer

My name Dženan is pronounced Jenan. I joined Kitware’s Carrboro, N.C. office as a Research and Development Engineer on the Medical Computing team in October 2014.

Since coming to Kitware, I have worked on image analysis and surgical guidance projects. To facilitate PET/CT guided needle biopsy, we developed SlicerPET software, involving CT-CT registration, needle tracking and tracker-CT registration. In skull correction surgery project we aim to develop quantitative shape measurement enabling optimal treatment planning and objective postoperative evaluation. We also investigated usage of ultrasound volume reconstruction for proper anatomical positioning of condyle/ramus segment in mandibular advancement orthognatic surgery.

I work with PET/CT pocket phantom and associated analysis tools in order to reduce SUV errors. I also contributed to ITK-SNAP, an open source 3D image viewer and segmentation tool. I participate in maintenance of ITK. I work on software for medical devices and robotic companies, most of which are covered by a non-disclosure agreements.

Between 2002 and 2007 I studied computer science at University of Sarajevo in Bosnia and Herzegovina. For a short time I was a software engineer for aNET and BSTelecom. I mostly worked on database-backed software with classic graphical and web user interface.

In May 2008 I moved to Siegen, Germany to begin a PhD in computer graphics at University of Siegen. I defended my PhD thesis in September 2014. My main focus were algorithms for vertebral body segmentation and diagnosis in magnetic resonance images. Side projects were brain tumor segmentation and dataset classification using neural networks.

  1. 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]
  2. 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]
  3. 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.
  4. 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.
  5. 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.
  6. 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]
  7. 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]
  8. D. Zukić, J. Vicory, M. McCormick, L. Wisse, G. Gerig, P. Yushkevich, and S. Aylward, "nD morphological contour interpolation," The Insight Journal, 2016. [URL]
  9. 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.
  10. 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]
  11. 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.
  12. 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]
  13. 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.
  14. D. Zukić, "An Efficient Inflation Method for Segmentation of Medical 3D Images," Ph.D. dissertation, University of Siegen, 2015. [URL]
  15. 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]
  16. 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]
  17. 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]
  18. 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]
  19. 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]
  20. 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]
  21. 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]
  22. 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]
  23. 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]
  24. 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]
  25. D. Zukić, "Neuronske mreže u vizuelizaciji CT snimaka," Elektrotehnički Fakultet, Univerzitet u Sarajevu, 2007. [URL]
  26. 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.