Research output per year
Research output per year
Personal profile
Biography
Jake has completed a Bachelor of Science (majoring in Engineering Science and Pharmacology), a Diploma of Physics, and a Masters of Physics (Medical Physics).
Jake is currently a PhD student in the field of Medical Physics at the University of Western Australia. He has a keen interest in the utilisation of artificial intelligence (AI) techniques to solve clinical challenges and improve the lives of patients. His current research focus is centred on the development of an automated segmentation framework for metastatic prostate lesions from 68Ga-PSMA-11 PET/CT scans.
Jake is a current lead and founding member of the UWA Machine Learning in Cancer Research group which provides students from a variety of fields with a forum to discuss their machine learning-related projects. This group was awarded the distinguished Award for Programs that Enhance Learning by the School of Physics, Mathematics and Computing in October of 2022. Jake is also a member of the Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) AI Working Group, tasked with preparing the college for the expected professional changes resulting from the clinical implementation of AI-based solutions.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research expertise keywords
- Prostate Cancer
- PSMA PET/CT
- Artificial intelligence
- Quantitative Imaging
- Machine Learning
- Medical Physics
- Nuclear Medicine
- Diagnostic Imaging
- Radiomics
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Delineation and agreement of FET PET biological volumes in glioblastoma: results of the nuclear medicine credentialing program from the prospective, multi-centre trial evaluating FET PET In Glioblastoma (FIG) study—TROG 18.06
Barry, N., Francis, R. J., Ebert, M. A., Koh, E. S., Rowshanfarzad, P., Hassan, G. M., Kendrick, J., Gan, H. K., Lee, S. T., Lau, E., Moffat, B. A., Fitt, G., Moore, A., Thomas, P., Pattison, D. A., Akhurst, T., Alipour, R., Thomas, E. L., Hsiao, E., Schembri, G. P., & 18 others, Nov 2023, In: European Journal of Nuclear Medicine and Molecular Imaging. 50, 13, p. 3970-3981 12 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
Prognostic utility of RECIP 1.0 with manual and AI-based segmentations in biochemically recurrent prostate cancer from [68Ga]Ga-PSMA-11 PET images
Kendrick, J., Francis, R. J., Hassan, G. M., Rowshan Farzad, P., Ong, J. SL., McCarthy, M. C., Alexander, S. & Ebert, M., Nov 2023, In: European Journal of Nuclear Medicine and Molecular Imaging. 50, 13, p. 4077-4086 10 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Prospective inter- and intra-tracer repeatability analysis of radiomics features in [68Ga]Ga-PSMA-11 and [18F]F-PSMA-1007 PET scans in metastatic prostate cancer
Kendrick, J., Francis, R., Hassan, G. M., Rowshan Farzad, P., Ong, J. S. L., Jeraj, R., Barry, N., Hagan, T. & Ebert, M., 2023, In: The British journal of radiology. 96, 1152, 20221178.Research output: Contribution to journal › Article › peer-review
Open Access -
Quantitative [68Ga]Ga-PSMA-11 PET Biomarkers for the analysis of Lesion-level Progression in Biochemically Recurrent Prostate Cancer – A Multicentre Study
Kendrick, J., Francis, R., Hassan, G. M., Rowshan Farzad, P., Ong, J. S. L., Barry, N., Rusanov, B. & Ebert, M., Dec 2023, In: Scientific Reports. 13, 1, 17673 .Research output: Contribution to journal › Article › peer-review
Open Access -
Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review
Rusanov, B., Hassan, G. M., Reynolds, M., Sabet, M., Kendrick, J., Rowshanfarzad, P. & Ebert, M., Sept 2022, In: Medical Physics. 49, 9, p. 6019-6054 36 p.Research output: Contribution to journal › Review article › peer-review
Open Access16 Citations (Scopus)
Projects
- 1 Active
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Conversion between brain cancer imaging modalities using generative AI
Ebert, M., Barry, N., Rusanov, B., Kendrick, J., Safdar, S., Rowshan Farzad, P. & Hassan, M.
Department of Health (Western Australia)
13/10/23 → 31/12/24
Project: Research
Prizes
Activities
- 1 Membership of professional association
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Australasian College of Physical Scientists & Engineers in Medicine - AI Working Group (External organisation)
Jake Kendrick (Member)
1 Jul 2021Activity: Memberships › Membership of professional association