Dženan Zukić

Dženan Zukić

Senior R&D Engineer

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

I have worked in medical image analysis as a computer scientist ever since I started my PhD in 2008. My PhD research involved brain tumor segmentation and focused on segmentation of vertebral bodies and diagnosis of certain diseases from magnetic resonance images. Since coming to Kitware, my experience has diversified. I worked on image-based guidance of biopsy needle, shape analysis of baby craniums from CT scans, quantitative PET/CT imaging, and pre-clinical ultrasound imaging.

I contributed to ITK-SNAP, an open source 3D image viewer and segmentation tool. I participate in maintenance of ITK. I frequently write specialized modules for 3D Slicer. I work on software for medical devices and robotic companies, most of which are covered by a non-disclosure agreements. I worked with many collaborators, both in my field and other fields of science.

Vertebral Column Segmentation and Computer Aided Diagnosis from routine MRI
Patients with back pain frequently undergo magnetic resonance imaging (MRI). Routine MRIs suffer low spatial resolution in Z axis. I rose up to the challenge of developing an algorithm to segment vertebral bodies in such images. With vertebrae segmented, it is possible to quantify three abnormalities: scoliosis (Cobb angle), spondylolisthesis (slip percentage) and vertebral fracture (compression percentage). These findings can aid a radiologist in the diagnosis. Additionally, the developed algorithm handles a large variability of MRI scanning parameters, as tested on images from multiple medical centers. For maximum impact, the software was written in a cross-platform manner and released as open source. For complete reproducibility, the image data as well as manual segmentations are made publicly available.

Image-Based Surgical Guidance
Surgical guidance and image-guided surgery system are powerful tools for surgeons to perform their procedures effectively. I have participated in software development of several surgical guidance systems using support from National Institutes of Health, including PET-CT guided needle biopsy and ultrasound-guided orthognathic surgery.

Analysis of Cranial Shape for Craniosynostosis Surgery
Craniosynostosis is a congenital condition characterized by premature fusion of the cranial sutures. CT is routinely used to confirm the diagnosis as well as to plan the corrective surgery. I have participated in development of software for determining the optimal postoperative cranial shape. I also processed the data in order to create the normative atlas with hundreds of normal cases. Aiming the surgery towards the closest normal shape instead of the mean cranial shape has the potential to reduce the surgery duration and shorten patient recovery time.

Calibration Software for Quantitative PET/CT Imaging
Multi-center clinical trials that use PET imaging need quantitatively comparable images to assess drug effectiveness. Many factors cause variability in PET intensity values. Scanner calibration and reconstructed image resolution variations are two important ones. We provide a quality assurance system using portable PET/CT ‘pocket’ phantoms and automated image analysis algorithms with the goal of reducing PET measurement variability. I was the main software developer in this project.

Pre-clinical 3D ultrasound imaging system
Current search for cancer drugs in part employs infecting small animals with cancer, then following disease progression when treated with different proposed drugs. To enable precise, quick and low-cost tumor size tracking we developed a system, which uses different 2D ultrasound probe moved by robot. Software controls movement of the ultrasound probe, tracks its position and stitches 2D images to construct full 3D image of the animal. I participated in algorithm development and software integration.

  1. 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.
  2. 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]
  3. 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]
  4. 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.
  5. 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.
  6. 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.
  7. 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]
  8. 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]
  9. D. Zukić, J. Vicory, M. McCormick, L. Wisse, G. Gerig, P. Yushkevich, and S. Aylward, "nD morphological contour interpolation," The Insight Journal, 2016. [URL]
  10. 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.
  11. 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]
  12. 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.
  13. 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]
  14. 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.
  15. D. Zukić, "An Efficient Inflation Method for Segmentation of Medical 3D Images," Ph.D. dissertation, University of Siegen, 2015. [URL]
  16. 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]
  17. 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]
  18. 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]
  19. 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]
  20. 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]
  21. 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]
  22. 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]
  23. 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]
  24. 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]
  25. 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]
  26. D. Zukić, "Neuronske mreže u vizuelizaciji CT snimaka," Elektrotehnički Fakultet, Univerzitet u Sarajevu, 2007. [URL]
  27. 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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