Dr Shakes Chandra

Lecturer

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology
shekhar.chandra@uq.edu.au
+61 7 336 58359

Overview

Shakes' expertise include image processing, machine learning, discrete tomography and medical image analysis. He received his Ph.D in Theoretical Physics from Monash University, Melbourne in 2010 on a discrete theory of the Radon transform that utilises circulant matrices. He did a post-doctoral fellowship with CSIRO, Brisbane within the biomedical imaging group on musculoskeletal imaging. More specifically, he developed deformable model and machine learning algorithms for knee, hip and shoulder joint segmentation for deployment on the Siemens Syngo platform. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Research Interests

  • Machine learning
    Dimensionality reduction and Deep Learning
  • Magnetic Resonance Imaging
    Making MRI faster and more affordable through better image reconstruction, processing and analysis.
  • Image Processing
    Image reconstruction, segmentation and registration.
  • Fractals and Chaos
    Applying fractals and chaos to image processing and computer science.
  • Number Theory
    Applying number theory to image processing and computer science.

Qualifications

  • Doctor of Philosophy, Monash University

Publications

  • Min, Hang, Chandra, Shekhar S, Crozier, Stuart and Bradley, Andrew P (2019) Multi-scale sifting for mammographic mass detection and segmentation. Biomedical Physics and Engineering Express, . doi:10.1088/2057-1976/aafc07

  • Sun, Jiayu and Chandra, Shekhar S. (2018). SPIFFY: A simpler image viewer for medical imaging. In: , , (297-301). . doi:10.1109/ITOEC.2018.8740656

  • Chandra, Shekhar S., Ruben, Gary, Jin, Jin, Li, Mingyan, Kingston, Andrew, Svalbe, Imants and Crozier, Stuart (2018) Chaotic Sensing. IEEE Transactions on Image Processing, 27 12: 1-1. doi:10.1109/TIP.2018.2864918

View all Publications

Supervision

  • Doctor Philosophy

  • Master Philosophy

  • Doctor Philosophy

View all Supervision

Available Projects

  • Magnetic resonance (MR) imaging has become an important non-invasive radiological modality for various clinical applications, such as cartilage assessment for Osteoarthritis and treatment planning for prostate cancer. MR images in 3D, while providing a wealth of anatomical information, including bones and soft tissue, are difficult to analyse due to the presence of a large number of complex structures. Thus, extracting meaningful clinical information without human interaction is a challenging task. Developing such automatic methods are important in order to reduce human errors and the time taken by clinicians in completing mundane tasks, such as marking or delineating 3D images by hand, from hours to just a few minutes by utilising computers.

    In this project, the student will develop novel algorithms to solve segmentation and detection problems for MR imaging that could possibly be deployed to MRI scanners and may eventually used for diagnostic purposes. The project will involve applying computer vision and machine learning techniques (including deep learning) to MR image processing and analysis.

View all Available Projects

Publications

Journal Article

Conference Publication

  • Sun, Jiayu and Chandra, Shekhar S. (2018). SPIFFY: A simpler image viewer for medical imaging. In: , , (297-301). . doi:10.1109/ITOEC.2018.8740656

  • Min, Hang, Chandra, Shekhar S., Dhungel, Neeraj, Crozier, Stuart and Bradley, Andrew P. (2017). Multi-scale mass segmentation for mammograms via cascaded random forests. In: Proceedings - International Symposium on Biomedical Imaging. 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, VIC, Australia, (113-117). 18 - 21 April 2017. doi:10.1109/ISBI.2017.7950481

  • Neubert, Aleš, Fripp, Jurgen, Chandra, Shekhar S., Engstrom, Craig and Crozier, Stuart (2016). Automated intervertebral disc segmentation using probabilistic shape estimation and active shape models. In: Tomaz Vrtovec, Jianhua Yao, Ben Glocker, Tobias Klinder, Alejandro Frangi, Guoyan Zheng and Shuo Li, Computational methods and clinical applications for spine imaging, Third International Workshop and Challenge, CSI 2015. Third International Workshop and Challenge, CSI 2015, Munich, Germany, (149-158). 5 October 2015. doi:10.1007/978-3-319-41827-8_15

  • Chandra, Shekhar S., Archchige, Ramitha, Ruben, Gary, Jin, Jin, Li, Mingyan, Kingston, Andrew M., Svalbe, Imants and Crozier, Stuart (2016). Finite radial reconstruction for magnetic resonance imaging: a theoretical study. In: 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016, Gold Coast, QLD, Australia, (). 30 November-2 December 2016. doi:10.1109/DICTA.2016.7797043

  • Neubert, Ales, Naser, Ibrahim, Paproki, Anthony, Engstrom, Craig, Fripp, Jurgen, Crozier, Stuart and Chandra, Shekhar S. (2016). Incremental shape learning of 3D surfaces of the knee, data from the osteoarthritis initiative. In: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, (881-884). 13-16 April, 2016. doi:10.1109/ISBI.2016.7493406

  • Neubert, Ales, Chandra, Shekhar S., Engstrom, Craig, Fripp, Jurgen and Crozier, Stuart (2015). Shape reconstruction using EM-ICP mesh registration and robust statistical shape models. In: Symposium on Statistical Shape Models and Applications Proceedings. Symposium on Statistical Shape Models Applications, Delemont, Switzerland, (25-25). 30 September - 2 October, 2015.

  • Dowling, J. A., Burdett, N., Greer, P. B., Sun, J., Parker, J., Pichler, P., Stanwell, P., Chandra, S., Rivest-Henault, D., Ghose, S., Salvado, O. and Fripp, J. (2014). Automatic Atlas Based Electron Density and Structure Contouring for MRI-based Prostate Radiation Therapy on the Cloud. In: Journal of Physics: Conference Series. XVII International Conference on the Use of Computers in Radiation Therapy, Melbourne, Australia, (012048.1-012048.6). 6–9 May 2013. doi:10.1088/1742-6596/489/1/012048

  • Yang, Zhengyi, Fripp, Jurgen, Engstrom, Craig, Chandra, Shekhar, Xia, Ying, Paproki, Anthony, Strudwick, Mark, Neubert, Ales and Crozier, Stuart (2014). Automatic Bone Segmentation for Shoulder {MRI} using Statistical Shape Models. In: Program Schedule with Recorded Oral Scientific Presentations. 2014 – Joint Annual Meeting ISMRM-ESMRMB, 22nd Scientific Meeting and Exhibition, Milan, Italy, (). 10-16 May 2014.

  • Dowling, Jason, Dang, K., Fox, Chris D., Chandra, S., Gill, Suki, Kron, T., D Pham, D. and Foroudi, F. (2014). Fast cine-magnetic resonance imaging point tracking for prostate cancer radiation therapy planning. In: XVII International Conference on the Use of Computers in Radiation Therapy (ICCR 2013). Proceedings. ICCR 2013: XVII International Conference on the Use of Computers in Radiation Therapy, Melbourme, VIC, Australia, (1-6). 6–9 May, 2013. doi:10.1088/1742-6596/489/1/012027

  • Svalbe, Imants, Kingston, Andrew, Guedon, Jeanpierre, Normand, Nicolas and Chandra, Shekhar S. (2013). Direct Inversion of Mojette Projections. In: 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings. 20th IEEE International Conference on Image Processing, ICIP 2013, Melbourne , Australia, (1036-1040). 15 - 18 September 2013. doi:10.1109/ICIP.2013.6738214

  • Xia, Ying, Chandra, Shakes, Salvado, Oliver, Fripp, Jurgen, Schwartz, Raphael, Lauer, Lars, Engstrom, Craig M. and Crozier, Stuart (2012). Automated bone segmentation and bone-cartilage interface extraction from MR images of the hip. In: ISMRM 20th Annual Meeting & Exhibition: Adapting MRI in a Changing World. International Society for Magnetic Resonance in Medicine, Melbourme, VIC, Australia, (). 5-11 May 2012.

  • Yang, Zhengyi, Crozier, Stuart, Engstrom, Craig, Xia, Ying, Neubert, Ales, Brancato, Tania, Schwarz, Raphael, Lauer, Lars, Fripp, Jurgen, Chandra, Shekhar and Salvado, Olivier (2012). Morphology-based interslice interpolation on manual segmentations of joint bones and muscles in MRI. In: 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA). 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Fremantle, WA, Australia, (). 3-5 December 2012. doi:10.1109/DICTA.2012.6411678

  • Chandra, Shekhar, Xia, Yinq, Engstrom, Craig, Schwarz, Raphael, Lauer, Lars, Crozier, Stuart, Salvado, Olivier and Fripp, Jurgen (2012). Unilateral hip joint segmentation with shape priors learned from missing data. In: 2012 9th IEEE International Symposium On Biomedical Imaging (ISBI). 9th IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, Spain, (1711-1714). 2-5 March 2012. doi:10.1109/ISBI.2012.6235909

  • Xia, Ying, Chandra, Shakes, Salvado, Olivier, Fripp, Jurgen, Schwarz, Raphael, Lauer, Lars, Engstrom, Craig and Crozier, Stuart (2011). Automated MR hip bone segmentation. In: International Conference on Digital Image Computing Techniques and Applications (DICTA). International Conference on Digital Image Computing Techniques and Applications (DICTA), Noosa, QLD, Australia, (25-30). 6-8 December 2011. doi:10.1109/DICTA.2011.13

  • Chandra, Shekhar, Dowling, Jason, Shen, Kaikai, Pluim, Josien, Greer, Peter, Salvado, Olivier and Fripp, Jurgen (2011). Automatic segmentation of the prostate in 3D magnetic resonance images using case specific deformable models. In: Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011). International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011, Noosa Heads, Qld., Australia, (7-12). 6-8 December 2011. doi:10.1109/DICTA.2011.10

  • Dowling, Jason A., Fripp, Jurgen, Chandra, Shekhar, Pluim, Josien P. W., Lambert, Jonathan, Parker, Joel, Denham, James, Greer, Peter B. and Salvado, Olivier (2011). Fast automatic multi-atlas segmentation of the prostate from 3D MR images. In: Madabhushi, A, Dowling, J, Huisman, H and Barratt, D, Prostate Cancer Imaging: Image Analysis and Image-Guided Interventions. 14th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011), Toronto, Canada, (10-21). 18-22 September 2011. doi:10.1007/978-3-642-23944-1_2

  • Svalbe, Imants and Chandra, Shekhar (2011). Growth of Discrete Projection Ghosts Created by Iteration. In: Isabelle Debled-Rennesson, Eric Domenjoud, Bertrand Kerautret and Philippe Even, Discrete Geometry for Computer Imagery: 16th IAPR International Conference, DGCI 2011. 16th International Conference on Discrete Geometry for Computer Imagery, Nancy France, (406-416). 6 - 8 April 2011. doi:10.1007/978-3-642-19867-0_34

  • Svalbe, Imants, Nazareth, Nikesh, Chandra, Shekhar and Normand, Nicolas (2010). On constructing minimal ghosts. In: Jian Zhang, Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010, Sydney, NSW Australia, (276-281). 01 - 03 December 2010. doi:10.1109/DICTA.2010.56

  • Chandra, S. and Svalbe, I. (2009). A fast number theoretic finite radon transform. In: Hao Shi, DICTA 2009 : 2009 digital image computing techniques and applications : proceedings. Digital Image Computing: Techniques and Applications, DICTA 2009, Melbourne, VIC Australia, (361-368). 1 - 3 December 2009. doi:10.1109/DICTA.2009.67

  • Chandra, Shekhar and Svalbe, Imants (2008). A method for removing cyclic artefacts in discrete tomography using latin squares. In: Pattern Recognition, 2008. ICPR 2008. 19th International Conference on. 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, Fl United States, (1702-1705). 8 - 11 Dec 2008. doi:10.1109/ICPR.2008.4761615

  • Chandra, Shekhar, Svalbe, Imants and Guedon, Jean-Pierre (2008). An exact, non-iterative Mojette inversion technique utilising ghosts. In: Discrete geometry for computer imagery : 14th IAPR international conference, DGCI 2008: Proceedings. 14th International Conference on Discrete Geometry for Computer Imagery, Lyon, France, (401-412). 16 - 18 April 2008. doi:10.1007/978-3-540-79126-3_36

  • Svalbe, Imants, Chandra, Shekhar, Kingston, Andrew and Guédon, Jean-Pierre (2006). Quantised angular momentum vectors and projection angle distributions for discrete radon transformations. In: Discrete Geometry for Computer Imagery - 13th International Conference, DGCI 2006, Proceedings. 13th International Conference on Discrete Geometry for Computer Imagery, DGCI 2006, , , (134-145). October 25, 2006-October 27, 2006.

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Magnetic resonance (MR) imaging has become an important non-invasive radiological modality for various clinical applications, such as cartilage assessment for Osteoarthritis and treatment planning for prostate cancer. MR images in 3D, while providing a wealth of anatomical information, including bones and soft tissue, are difficult to analyse due to the presence of a large number of complex structures. Thus, extracting meaningful clinical information without human interaction is a challenging task. Developing such automatic methods are important in order to reduce human errors and the time taken by clinicians in completing mundane tasks, such as marking or delineating 3D images by hand, from hours to just a few minutes by utilising computers.

    In this project, the student will develop novel algorithms to solve segmentation and detection problems for MR imaging that could possibly be deployed to MRI scanners and may eventually used for diagnostic purposes. The project will involve applying computer vision and machine learning techniques (including deep learning) to MR image processing and analysis.