Dr Shakes Chandra
Dr

Shakes Chandra

Email: 
Phone: 
+61 7 336 58359

Background

Shakes an imaging expert that leads a strong deep learning, artificial intelligence (AI) focused research team interested in medical image analysis and signal/image processing applied to many areas of science and medicine. He received his Ph.D in Theoretical Physics from Monash University, Melbourne and has been involved in applying machine learning in medical imaging for over a decade.

Shakes’ past work has involved developing shape model-based algorithms for knee, hip and shoulder joint segmentation that is being developed and deployed as a product on the Siemens syngo.via platform. More recent work involves deep learning based algorithms for semantic segmentation and manifold learning of imaging data. Broadly, he is interested in understanding and developing the mathematical basis of imaging, image analysis algorithms and physical systems. He has developed algorithms that utilise exotic mathematical structures such as fractals, turbulence, group theoretic concepts and number theory in the image processing approaches that he has developed.

He is currently a Senior Lecturer and leads a team of 20+ researchers working image analysis and AI research across healthcare and medicine. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Availability

Dr Shakes Chandra is:
Available for supervision

Fields of research

Artificial intelligence Biomedical engineering Biomedical imaging Combinatorics and discrete mathematics (excl. physical combinatorics) Computational imaging Computer vision and multimedia computation Deep learning Engineering Image processing Information and Computing Sciences Machine learning Mathematical Sciences Pure mathematics Theory of computation

Qualifications

  • Doctor of Philosophy, Monash University

Research interests

  • Magnetic Resonance Imaging

    Making MRI faster and more affordable through better image reconstruction, processing and analysis.

  • Image Processing

    Image reconstruction, segmentation and registration.

  • Deep learning

    Dimensionality reduction, machine learning and Artificial Intelligence

  • Fractals and Chaos

    Applying fractals and chaos to image processing and computer science.

  • Number Theory

    Applying number theory to image processing and computer science.

  • Medical Image Analysis

    Medical image segmentation and shape analysis

Research impacts

Times Higher Education - A joint effort: machine learning’s search for the first MRI-based biomarker of osteoarthritis

UQNews - Making magnetic resonance imaging (MRI) faster using fractals and turbulence.

Search Professor Shakes Chandra’s works on UQ eSpace

98 works between 2006 and 2025
All (98) Journal Article (49) Conference Publication (46) Other Outputs (3)

41 - 60 of 98 works

2021

Journal Article

Automated analysis of immediate reliability of T2 and T2* relaxation times of hip joint cartilage from 3 T MR examinations

Bugeja, Jessica M., Chandra, Shekhar S., Neubert, Aleš, Fripp, Jurgen, Lockard, Carly A., Ho, Charles P., Crozier, Stuart and Engstrom, Craig (2021). Automated analysis of immediate reliability of T2 and T2* relaxation times of hip joint cartilage from 3 T MR examinations. Magnetic Resonance Imaging, 82, 42-54. doi: 10.1016/j.mri.2021.06.008

Automated analysis of immediate reliability of T2 and T2* relaxation times of hip joint cartilage from 3 T MR examinations

2021

Journal Article

Bespoke fractal sampling patterns for discrete Fourier space via the kaleidoscope transform

White, Jacob Michael, Crozier, Stuart and Chandra, Shekhar Suresh (2021). Bespoke fractal sampling patterns for discrete Fourier space via the kaleidoscope transform. IEEE Signal Processing Letters, 14 (8), 1-5. doi: 10.1109/lsp.2021.3116510

Bespoke fractal sampling patterns for discrete Fourier space via the kaleidoscope transform

2021

Journal Article

The detection of mild traumatic brain injury in paediatrics using artificial neural networks

Ellethy, Hanem, Chandra, Shekhar S. and Nasrallah, Fatima A. (2021). The detection of mild traumatic brain injury in paediatrics using artificial neural networks. Computers in Biology and Medicine, 135 104614, 1-9. doi: 10.1016/j.compbiomed.2021.104614

The detection of mild traumatic brain injury in paediatrics using artificial neural networks

2021

Journal Article

Deep learning in magnetic resonance image reconstruction

Chandra, Shekhar S., Bran Lorenzana, Marlon, Liu, Xinwen, Liu, Siyu, Bollmann, Steffen and Crozier, Stuart (2021). Deep learning in magnetic resonance image reconstruction. Journal of Medical Imaging and Radiation Oncology, 65 (5) 1754-9485.13276, 564-577. doi: 10.1111/1754-9485.13276

Deep learning in magnetic resonance image reconstruction

2021

Conference Publication

Can3d: Fast 3D knee mri segmentation via compact context aggregation

Dai, Wei, Woo, Boyeong, Liu, Siyu, Marques, Matthew, Tang, Fangfang, Crozier, Stuart, Engstrom, Craig and Chandra, Shekhar (2021). Can3d: Fast 3D knee mri segmentation via compact context aggregation. 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 13-16 April 2021. Piscataway, NJ United States: IEEE. doi: 10.1109/isbi48211.2021.9433784

Can3d: Fast 3D knee mri segmentation via compact context aggregation

2021

Journal Article

On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks

Liu, Xinwen, Wang, Jing, Sun, Hongfu, Chandra, Shekhar S, Crozier, Stuart and Liu, Feng (2021). On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks. Magnetic resonance imaging, 77, 159-168. doi: 10.1016/j.mri.2020.12.019

On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks

2021

Journal Article

Discrete element and finite element methods provide similar estimations for hip joint contact mechanics during walking gait

Li, Mao, Venäläinen, Mikko S., Chandra, Shekhar S., Patel, Rushabh, Fripp, Jurgen, Engstrom, Craig, Korhonen, Rami K., Töyräs, Juha and Crozier, Stuart (2021). Discrete element and finite element methods provide similar estimations for hip joint contact mechanics during walking gait. Journal of Biomechanics, 115 110163, 1-11. doi: 10.1016/j.jbiomech.2020.110163

Discrete element and finite element methods provide similar estimations for hip joint contact mechanics during walking gait

2021

Journal Article

The application of statistical shape modeling for lung morphology in aerosol inhalation dosimetry

Xi, Jinxiang, Talaat, Mohamed, Si, Xiuhua April and Chandra, Shekhar (2021). The application of statistical shape modeling for lung morphology in aerosol inhalation dosimetry. Journal of Aerosol Science, 151 105623, 105623. doi: 10.1016/j.jaerosci.2020.105623

The application of statistical shape modeling for lung morphology in aerosol inhalation dosimetry

2021

Conference Publication

End-to-end ugly duckling sign detection for melanoma identification with transformers

Yu, Zhen, Mar, Victoria, Eriksson, Anders, Chandra, Shakes, Bonnington, Paul, Zhang, Lei and Ge, Zongyuan (2021). End-to-end ugly duckling sign detection for melanoma identification with transformers. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, Strasbourg, France, 27 September-1 October 2021. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-030-87234-2_17

End-to-end ugly duckling sign detection for melanoma identification with transformers

2020

Journal Article

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI

Min, Hang, McClymont, Darryl, Chandra, Shekhar S., Crozier, Stuart and Bradley, Andrew P. (2020). Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI. Biomedical Physics and Engineering Express, 6 (6) 065027, 065027. doi: 10.1088/2057-1976/abc45c

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI

2020

Journal Article

Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system

Li, Mao, Shan, Shanshan, Chandra, Shekhar S., Liu, Feng and Crozier, Stuart (2020). Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system. Medical Physics, 47 (9) mp.14382, 4303-4315. doi: 10.1002/mp.14382

Fast geometric distortion correction using a deep neural network: implementation for the 1 Tesla MRI-Linac system

2020

Conference Publication

Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI

Liu, Xinwen, Wang, Jing, Tang, Fangfang, Chandra, Shekhar S., Liu, Feng and Crozier, Stuart (2020). Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI. ISMRM & SMRT Virtual Conference & Exhibition, 2020, Online, 8-14 August 2020.

Deep simultaneous optimization of sampling and reconstruction for multi-contrast MRI

2020

Journal Article

Simultaneous super-resolution and contrast synthesis of routine clinical magnetic resonance images of the knee for improving automatic segmentation of joint cartilage: data from the Osteoarthritis Initiative

Neubert, Aleš, Bourgeat, Pierrick, Wood, Jason, Engstrom, Craig, Chandra, Shekhar S., Crozier, Stuart and Fripp, Jurgen (2020). Simultaneous super-resolution and contrast synthesis of routine clinical magnetic resonance images of the knee for improving automatic segmentation of joint cartilage: data from the Osteoarthritis Initiative. Medical Physics, 47 (10) mp.14421, 4939-4948. doi: 10.1002/mp.14421

Simultaneous super-resolution and contrast synthesis of routine clinical magnetic resonance images of the knee for improving automatic segmentation of joint cartilage: data from the Osteoarthritis Initiative

2020

Conference Publication

Fast high dynamic range MRI by Contrast Enhancement Networks

Marques, Matthew, Engstrom, Craig, Fripp, Jurgen, Crozier, Stuart and Chandra, Shekhar S. (2020). Fast high dynamic range MRI by Contrast Enhancement Networks. 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, United States, 3-7 April 2020. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/isbi45749.2020.9098373

Fast high dynamic range MRI by Contrast Enhancement Networks

2020

Conference Publication

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

Min, Hang, Wilson, Devin, Huang, Yinhuang, Liu, Siyu, Crozier, Stuart, Bradley, Andrew P. and Chandra, Shekhar S. (2020). Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN. 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, United States, 3-7 April 2020. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/isbi45749.2020.9098732

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

2019

Journal Article

Multi-scale sifting for mammographic mass detection and segmentation

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, 5 (2) 025022, 025022. doi: 10.1088/2057-1976/aafc07

Multi-scale sifting for mammographic mass detection and segmentation

2018

Journal Article

Local contrast-enhanced MR images via high dynamic range processing

Chandra, Shekhar S., Engstrom, Craig, Fripp, Jurgen, Neubert, Ales, Jin, Jin, Walker, Duncan, Salvado, Olivier, Ho, Charles and Crozier, Stuart (2018). Local contrast-enhanced MR images via high dynamic range processing. Magnetic Resonance in Medicine, 80 (3), 1206-1218. doi: 10.1002/mrm.27109

Local contrast-enhanced MR images via high dynamic range processing

2018

Journal Article

Chaotic Sensing

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) 8432445, 1-1. doi: 10.1109/TIP.2018.2864918

Chaotic Sensing

2018

Journal Article

A lightweight rapid application development framework for biomedical image analysis

Chandra, Shekhar S., Dowling, Jason A., Engstrom, Craig, Xia, Ying, Paproki, Anthony, Neubert, Aleš, Rivest-Hénault, David, Salvado, Olivier, Crozier, Stuart and Fripp, Jurgen (2018). A lightweight rapid application development framework for biomedical image analysis. Computer Methods and Programs in Biomedicine, 164, 193-205. doi: 10.1016/j.cmpb.2018.07.011

A lightweight rapid application development framework for biomedical image analysis

2018

Conference Publication

SPIFFY: a simpler image viewer for medical imaging

Sun, Jiayu and Chandra, Shekhar S. (2018). SPIFFY: a simpler image viewer for medical imaging. 4th Information Technology and Mechatronics Engineering Conference (ITOEC2018), Chongqing, China, 14-16 December 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ITOEC.2018.8740656

SPIFFY: a simpler image viewer for medical imaging

Current funding

  • 2022 - 2025
    Advancing the visualisation and quantification of nephrons with MRI
    ARC Discovery Projects
    Open grant
  • 2020 - 2026
    PREDICT-TBI - PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury: the value of Magnetic Resonance Imaging
    NHMRC MRFF Traumatic Brain Injury Mission
    Open grant

Past funding

  • 2022 - 2025
    Robust, valid and interpretable deep learning for quantitative imaging
    ARC Linkage Projects
    Open grant
  • 2021 - 2024
    ChondralHealth Productization: Automated Musculoskeletal MR Image Analysis Algorithms
    Siemens Healthcare Pty Ltd
    Open grant
  • 2021 - 2024
    Osteoarthritis Compass: Personalized prediction of disease onset and progression. (NHMRC Ideas Grant administered by Griffith University)
    Griffith University
    Open grant
  • 2018 - 2022
    MR Hip Intervention and Planning System to enhance clinical and surgical outcomes
    NHMRC Development Grant
    Open grant

Availability

Dr Shakes Chandra is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Available projects

  • Machine learning applied to 3D magnetic resonance images

    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.

Supervision history

Current supervision

Completed supervision

Enquiries

For media enquiries about Dr Shakes Chandra's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au