Post Doctoral – Fellow at University of California, San Diego, United States
Jiyo S. Athertya is a passionate biomedical engineer and researcher with a strong foundation in medical image processing and ultrashort echo time (UTE) MRI technologies. With an emphasis on advancing early diagnostics and monitoring of musculoskeletal and neurological diseases, Jiyo has made significant contributions to the fields of MRI reconstruction, neuroimaging, and radiomics. He specializes in the design and development of innovative MRI techniques that enhance diagnostic sensitivity, particularly in degenerative spine disorders and neurodegenerative conditions like Alzheimer’s disease. His interdisciplinary approach combines engineering design, image analysis, and machine learning, aiming to bridge the gap between clinical imaging and precision diagnostics.
Profile
Scopus
Education
Jiyo earned his Ph.D. in Engineering Design from the Indian Institute of Technology Madras in 2018, where he focused on advanced imaging studies of the human spine. His doctoral work included creating algorithms for the segmentation and classification of vertebral deformities using both CT and MR images. Prior to this, he completed a Master of Engineering in Biomedical Engineering from the College of Engineering, Anna University in 2012, where his thesis centered on 3D CT image reconstruction of the vertebral column. His foundational education in Electrical and Electronics Engineering, completed in 2010 at Anna University, provided him with a robust technical base in signal analysis and instrumentation.
Experience
Jiyo is currently a postdoctoral researcher at UC San Diego, where he leads investigations into UTE-MRI techniques for improved neuroimaging and myelin quantification. He plays a pivotal role in developing quantitative MRI analysis pipelines, collaborating across disciplines, and mentoring junior researchers. Since 2022, he has also served as a Health Science Research Specialist at the VA Hospital San Diego, where he conducts MRI scanning of musculoskeletal tissues and participates in histological analyses in neurological studies. His earlier experience as a graduate research assistant at IIT-Madras further honed his skills in algorithm design, vertebral segmentation, and the analysis of spinal degenerative markers.
Research Interest
Jiyo’s research spans medical image processing, machine learning, radiomics, and deep learning applications in MRI. His current focus lies in advancing UTE MRI methodologies for detecting microstructural tissue properties such as myelin content in the brain, especially relevant to Alzheimer’s and traumatic brain injury models. He is particularly interested in automating diagnostic processes using AI, improving classification performance through data augmentation and feature optimization, and integrating fuzzy logic and soft computing in medical diagnostics. His investigations extend to spine imaging, Modic changes, and structural recovery in intervertebral discs.
Award
Jiyo’s research excellence has been acknowledged with several prestigious awards. He received the ISMRM Trainee Stipend for 2022–2024 and was honored with the Outstanding Author Award in 2024 for his publication on myelin water quantification in multiple sclerosis. He has been a finalist in the Postdoc Power Pitch competition and delivered an invited talk at UCSD’s Radiology Research+Education Seminar Series. Additionally, his presence at major conferences like ISMRM and EYH reflects his active engagement with the scientific community and dedication to public education in medical imaging.
Publication
Jiyo has an impressive publication record in peer-reviewed journals. Some selected works include:
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Athertya, Jiyo S., & Kumar, G. S. (2016). “Automatic segmentation of vertebral contours from CT images using fuzzy corners.” Computers in Biology and Medicine, 72, 75–89. [Cited by 45 articles]
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Athertya, Jiyo S., & Kumar, G. S. (2021). “Classification of certain vertebral degenerations using MRI image features.” Biomedical Physics & Engineering Express, 7(4), 045013. [Cited by 32 articles]
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Afsahi, A. M., Athertya, J., et al. (2022). “High-contrast lumbar spinal bone imaging using a 3D slab-selective UTE sequence.” Frontiers in Endocrinology, 12, 800398. [Cited by 29 articles]
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Jang, H., Athertya, J. S., et al. (2022). “UTE-QSM with 3D cones trajectory in human brain.” Frontiers in Neuroscience, 16, 1033801. [Cited by 18 articles]
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Athertya, Jiyo S., et al. (2023). “Detection of iron oxide nanoparticle-labeled stem cells using UTE.” Quantitative Imaging in Medicine and Surgery, 13(2), 585. [Cited by 22 articles]
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Moazamian, D., Athertya, J. S., et al. (2024). “Assessment of Achilles tendon using UTE-MRI T1 and MT modeling in psoriatic arthritis.” NMR in Biomedicine, 37(1), e5040. [Cited by 17 articles]
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Athertya, Jiyo S., et al. (2024). “High contrast cartilaginous endplate imaging in spine using 3D DIR-UTE.” Skeletal Radiology, 53(5), 881–890. [Cited by 10 articles]
Conclusion
Jiyo S. Athertya stands as a leading figure in biomedical imaging research, bringing innovative MRI techniques from theory to practice. His integrated approach in engineering and clinical imaging not only advances diagnostic capabilities but also fosters future innovation through mentorship and collaboration. With a clear vision for translational research, he continues to shape the field of neuroimaging and musculoskeletal diagnostics, making significant strides in both academic and clinical domains.