Dr Prabhakar Ramachandran
Dr

Prabhakar Ramachandran

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Background

Dr Prabhakar Ramachandran is the Director of Medical Physics at the Princess Alexandra Hospital (Ipswich Road). He has post-graduate degrees in Medical Physics, Electronics Engineering, and Computer Science. He earned his PhD from the All India Institute of Medical Sciences, New Delhi. He holds accreditation in Radiotherapy QA from the Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) and in Radiation Safety from the Australasian Radiation Protection Society Inc (ARPS). He is also board certified by the American Board of Radiology. His research interests include real-time dosimetry, treatment planning, 4D-imaging, radiation dosimetry, and developing deep learning models for Gamma Knife radiotherapy.

Availability

Dr Prabhakar Ramachandran is:
Available for supervision

Research interests

  • Radiation Dosimetry

Search Professor Prabhakar Ramachandran’s works on UQ eSpace

53 works between 2006 and 2024
All (53) Journal Article (50) Book Chapter (1) Conference Publication (2)

1 - 20 of 53 works

2024

Journal Article

Radio-opaque contrast agents for liver cancer targeting with KIM during radiation therapy (ROCK-RT): an observational feasibility study

Plant, Natalie, Mylonas, Adam, Sengupta, Chandrima, Nguyen, Doan Trang, Silvester, Shona, Pryor, David, Greer, Peter, Lee, Yoo Young, Ramachandran, Prabhakar, Seshadri, Venkatakrishnan, Trada, Yuvnik, Khor, Richard, Wang, Tim, Hardcastle, Nicholas and Keall, Paul (2024). Radio-opaque contrast agents for liver cancer targeting with KIM during radiation therapy (ROCK-RT): an observational feasibility study. Radiation Oncology, 19 (1) 139, 1. doi: 10.1186/s13014-024-02524-4

Radio-opaque contrast agents for liver cancer targeting with KIM during radiation therapy (ROCK-RT): an observational feasibility study

2024

Journal Article

A cost-effective breath-hold coaching camera system for patients undergoing external beam radiotherapy

Mehta, Akash, Horgan, Emma, Ramachandran, Prabhakar and Noble, Christopher (2024). A cost-effective breath-hold coaching camera system for patients undergoing external beam radiotherapy. Journal of Medical Physics, 49 (4), 502-509. doi: 10.4103/jmp.jmp_101_24

A cost-effective breath-hold coaching camera system for patients undergoing external beam radiotherapy

2024

Conference Publication

Enhancing Gamma Knife CBCT Image Quality Using Pix2Pix Generative Adversarial Networks

Ramachandran, Prabhakar, Colbert, Zachery, Anderson, Darcie, Fielding, Andrew, Arrington, Daniel and Foote, Matthew (2024). Enhancing Gamma Knife CBCT Image Quality Using Pix2Pix Generative Adversarial Networks. ESTRO meets Asia 2024, Kuala Lumpur, Malaysia, 23-25 August 2024. Shannon, Ireland: Elsevier. doi: 10.1016/s0167-8140(24)03134-7

Enhancing Gamma Knife CBCT Image Quality Using Pix2Pix Generative Adversarial Networks

2024

Journal Article

Utility of 68Ga-DOTATATE PET-MRI for Gamma Knife® stereotactic radiosurgery treatment planning for meningioma

Ratnayake, Gishan, Huo, Michael, Mehta, Akash, Ramachandran, Prabhakar, Pinkham, Mark B., Law, Phillip, Watkins, Trevor, Olson, Sarah, Hall, Bruce, Brown, Simon, Lusk, Ryan, Jones, Catherine, O’Mahoney, Eoin, McGill, George and Foote, Matthew C. (2024). Utility of 68Ga-DOTATATE PET-MRI for Gamma Knife® stereotactic radiosurgery treatment planning for meningioma. British Journal of Radiology, 97 (1153), 180-185. doi: 10.1093/bjr/tqad026

Utility of 68Ga-DOTATATE PET-MRI for Gamma Knife® stereotactic radiosurgery treatment planning for meningioma

2024

Journal Article

The first clinical implementation of real-time 6 degree-of-freedom image-guided radiotherapy for liver SABR patients

Sengupta, Chandrima, Trang Nguyen, Doan, Moodie, Trevor, Mason, Daniel, Luo, Jianjie, Causer, Trent, Fan Liu, Sau, Brown, Elizabeth, Inskip, Lauren, Hazem, Maryam, Chao, Menglei, Wang, Tim, Lee, Yoo Y, van Gysen, Kirsten, Sullivan, Emma, Cosgriff, Eireann, Ramachandran, Prabhakar, Poulsen, Per, Booth, Jeremy, O'Brien, Ricky, Greer, Peter and Keall, Paul (2024). The first clinical implementation of real-time 6 degree-of-freedom image-guided radiotherapy for liver SABR patients. Radiotherapy and Oncology, 190 110031, 110031-190. doi: 10.1016/j.radonc.2023.110031

The first clinical implementation of real-time 6 degree-of-freedom image-guided radiotherapy for liver SABR patients

2023

Journal Article

Design and development of a low-cost integrated dosimeter for external beam dosimetry in radiation oncology

Chant, Tim and Ramachandran, Prabhakar (2023). Design and development of a low-cost integrated dosimeter for external beam dosimetry in radiation oncology. Journal of Medical Physics, 48 (4), 392-397. doi: 10.4103/jmp.jmp_107_23

Design and development of a low-cost integrated dosimeter for external beam dosimetry in radiation oncology

2023

Journal Article

Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept

Shields, Benjamin and Ramachandran, Prabhakar (2023). Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept. Physical and Engineering Sciences in Medicine, 46 (3), 1321-1330. doi: 10.1007/s13246-023-01302-y

Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept

2023

Journal Article

Auto-segmentation of thoracic organs in CT scans of breast cancer patients using a 3D U-Net cascaded into PatchGANs

Colbert, Zachery Morton and Ramachandran, Prabhakar (2023). Auto-segmentation of thoracic organs in CT scans of breast cancer patients using a 3D U-Net cascaded into PatchGANs. Biomedical Physics and Engineering Express, 9 (5) 055011. doi: 10.1088/2057-1976/ace631

Auto-segmentation of thoracic organs in CT scans of breast cancer patients using a 3D U-Net cascaded into PatchGANs

2023

Conference Publication

Machine learning to predict local failure in melanoma brain metastases treated with radiosurgery

Shanker, M., Ramachandran, P., Motley, R., Huo, M., Foote, M. and Pinkham, M. (2023). Machine learning to predict local failure in melanoma brain metastases treated with radiosurgery. ESTRO 2023, Vienna, Austria, 13 - 16 May 2023. Shannon, Ireland: Elsevier. doi: 10.1016/s0167-8140(23)67001-x

Machine learning to predict local failure in melanoma brain metastases treated with radiosurgery

2023

Journal Article

Assessment of optimizers and their performance in autosegmenting lung tumors

Ramachandran, Prabhakar, Eswarlal, Tamma, Lehman, Margot and Colbert, Zachery (2023). Assessment of optimizers and their performance in autosegmenting lung tumors. Journal of Medical Physics, 48 (2), 129-135. doi: 10.4103/jmp.jmp_54_23

Assessment of optimizers and their performance in autosegmenting lung tumors

2023

Journal Article

Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation

Colbert, Zachery Morton, Arrington, Daniel, Foote, Matthew, Gårding, Jonas, Fay, Dominik, Huo, Michael, Pinkham, Mark and Ramachandran, Prabhakar (2023). Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation. Biomedical Physics and Engineering Express, 10 (2) 025004, 1-10. doi: 10.1088/2057-1976/ad17a7

Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation

2023

Journal Article

Investigation of computed tomography numbers on multiple imaging systems using single and multislice methods

Ramachandran, Prabhakar, Mehta, Akash, Arrington, Daniel, Motley, Ryan, Seshadri, Venkatakrishnan, Anderson, Darcie, Lehman, Margot and Perrett, Ben (2023). Investigation of computed tomography numbers on multiple imaging systems using single and multislice methods. Journal of Medical Physics, 48 (1) 26, 1-12. doi: 10.4103/jmp.jmp_3_23

Investigation of computed tomography numbers on multiple imaging systems using single and multislice methods

2023

Journal Article

Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture

Mehta, Akash, Lehman, Margot and Ramachandran, Prabhakar (2023). Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture. Journal of Cancer Research and Therapeutics, 19 (2), 289-298. doi: 10.4103/jcrt.jcrt_119_21

Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture

2022

Journal Article

Autosegmentation of brain metastases using 3D FCNN models and methods to manage GPU memory limitations

Bognar, Joshua and Ramachandran, Prabhakar (2022). Autosegmentation of brain metastases using 3D FCNN models and methods to manage GPU memory limitations. Biomedical Physics and Engineering Express, 8 (6) 065027, 1-13. doi: 10.1088/2057-1976/ac9b5b

Autosegmentation of brain metastases using 3D FCNN models and methods to manage GPU memory limitations

2022

Journal Article

A framework for exactrac dynamic commissioning for stereotactic radiosurgery and stereotactic ablative radiotherapy

Ramachandran, Prabhakar, Perrett, Ben, Ukath, Jaysree, Horgan, Emma and Noble, Chris (2022). A framework for exactrac dynamic commissioning for stereotactic radiosurgery and stereotactic ablative radiotherapy. Journal of Medical Physics, 47 (4), 398-408. doi: 10.4103/jmp.jmp_67_22

A framework for exactrac dynamic commissioning for stereotactic radiosurgery and stereotactic ablative radiotherapy

2022

Book Chapter

Role of artificial intelligence in automatic segmentation of brain metastases for radiotherapy

Ramachandran, Prabhakar, Seshadri, Venkatakrishnan, Perrett, Ben, Mehta, Akash, Fontanarosa, Davide, Pinkham, Mark and Foote, Matthew (2022). Role of artificial intelligence in automatic segmentation of brain metastases for radiotherapy. Artificial intelligence in cancer diagnosis and prognosis, Volume 3: Brain and prostate cancer. (pp. 4-1-4-23) edited by Ayman El-Baz and Jasjit S Suri. Bristol, U.K. : IOP Publishing. doi: 10.1088/978-0-7503-3603-1ch4

Role of artificial intelligence in automatic segmentation of brain metastases for radiotherapy

2022

Journal Article

A direct comparison of the optically stimulated luminescent properties of BeO and Al2O3 for clinical in-vivo dosimetry

Broadhead, Benjamin, Noble, Christopher and Ramachandran, Prabhakar (2022). A direct comparison of the optically stimulated luminescent properties of BeO and Al2O3 for clinical in-vivo dosimetry. Physical and Engineering Sciences in Medicine, 45 (3), 859-866. doi: 10.1007/s13246-022-01155-x

A direct comparison of the optically stimulated luminescent properties of BeO and Al2O3 for clinical in-vivo dosimetry

2022

Journal Article

Comparison and validation of multiple detectors against monte carlo simulation for the use of small-field dosimetry

Ramachandran, Prabhakar, Parveen, Nazia, Seshadri, Venkatakrishnan, Perrett, Ben and Fielding, Andrew (2022). Comparison and validation of multiple detectors against monte carlo simulation for the use of small-field dosimetry. Journal of Medical Physics, 47 (3), 235-242. doi: 10.4103/jmp.jmp_35_22

Comparison and validation of multiple detectors against monte carlo simulation for the use of small-field dosimetry

2022

Journal Article

A feasibility study on the development and use of a deep learning model to automate real-time monitoring of tumor position and assessment of interfraction fiducial marker migration in prostate radiotherapy patients

Motley, Ryan, Fielding, Andrew L and Ramachandran, Prabhakar (2022). A feasibility study on the development and use of a deep learning model to automate real-time monitoring of tumor position and assessment of interfraction fiducial marker migration in prostate radiotherapy patients. Biomedical Physics and Engineering Express, 8 (3) 035009. doi: 10.1088/2057-1976/ac34da

A feasibility study on the development and use of a deep learning model to automate real-time monitoring of tumor position and assessment of interfraction fiducial marker migration in prostate radiotherapy patients

2021

Journal Article

Automatic detection and tracking of marker seeds implanted in prostate cancer patients using a deep learning algorithm

Amarsee, Keya, Ramachandran, Prabhakar, Fielding, Andrew, Lehman, Margot, Noble, Christopher, Perrett, Ben and Ning, Daryl (2021). Automatic detection and tracking of marker seeds implanted in prostate cancer patients using a deep learning algorithm. Journal of Medical Physics, 46 (2), 80-87. doi: 10.4103/jmp.JMP_117_20

Automatic detection and tracking of marker seeds implanted in prostate cancer patients using a deep learning algorithm

Past funding

  • 2021 - 2023
    ACRF Facility for Targeted Radiometals in Cancer (AFTRiC)
    Australian Cancer Research Foundation
    Open grant

Availability

Dr Prabhakar Ramachandran is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Investigation into assessment methods of heterogeneity within MR and MRS images of brain tumours treated with Leksell Gamma Knife and their predictive value for treatment outcome

    Associate Advisor

Enquiries

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