Vasantha Kumar Venugopal

I am an experienced radiologist with a strong background in clinical practice, digital health innovation, and academic leadership. Currently, as an Adjunct Professor at the School of AI, Amrita Medical College and Hospital, I lead impactful healthcare AI projects aimed at clinical deployment, bridge the gap between clinicians and AI scientists, and mentor students in producing high-impact research and publications in AI and medicine. My work focuses on fostering collaborations between academia and industry while training the next generation of healthcare AI innovators.

In addition, I serve as a Consultant Radiologist with DGRAD Teleradiology Group, providing expert imaging interpretations remotely. My role involves delivering precise and actionable insights across diverse clinical settings, ensuring high-quality patient care.

Until recently, I held the role of Chief Medical Officer (CMO), where I led the deployment of multiple AI-driven solutions in major hospitals globally. This work significantly enhanced clinical workflows and improved patient outcomes through cutting-edge technology. My leadership experience in this role helped shape the integration of AI into real-world healthcare settings, emphasizing reliability, fairness, and safety.

I also hold an honorary position as Professor of Practice at Chettinad Academy of Research and Education, associated with Chettinad Hospitals, where I contribute to academic and research activities, enriching the learning experience for students and fostering innovation in healthcare

My combined roles as Adjunct Professor and Radiologist, along with my recent CMO experience, allow me to offer a unique perspective on healthcare delivery, blending hands-on clinical expertise with innovative technological approaches. My passion lies in teaching, mentoring, and advancing the integration of AI into healthcare. I have led numerous research studies and initiatives that evaluate the performance and safety of AI solutions in clinical settings.

Previously, as an Assistant Professor at a top-tier medical college, I contributed to the development of future healthcare professionals by sharing my expertise in radiology and its practical applications.

• IRIA Innovation Award - Issued by Indian Radiology and Imaging Association · Nov 2021 - National-level Award given to honor the Radiologist who has made the most significant contribution to innovative practices in radiology.
• Aunt Minnie’s Roadies award for the most viewed scientific abstract in the Artificial Intelligence category at RSNA 2019.
• RSNA travel award, 97th RSNA meeting, Chicago, 2011.
• ICMR international travel grant for oral presentation at RSNA 2010, Chicago.

• Venugopal, V. K. 3D Printing and Postprocessing. In Comprehensive Textbook of Clinical Radiology Volume I: Principles of Clinical Radiology, Multisystem Diseases & Head and Neck (p. 320). Elsevier Health Sciences.
• Mahajan, V., Venugopal, V. K., & Takhar, R. (2023). In Bharat Aggarwal (Ed.), Textbook of Radiology and Imaging, Volume 1 (pp. 125-134). Elsevier Health Sciences.
• Nasser, N. S., Arora, K., Venugopal, V. K., Mahajan, V., & Mahajan, H. (2023). In Manas Panigrahi, Suchanda Bhattacharjee, & N. Muthukumar (Eds.), Progress in Clinical Neurosciences, Volume 35 (pp. 320-335). Thieme.
• Mahajan, V., & Venugopal, V. K. (2020). In Artificial Intelligence: Applications in Healthcare Delivery (pp. 11-20). Taylor & Francis.

1. Yang, Y. X. C., Yee, S. Y., Tan, T. S. E., Koh, K. K. N., Goh, A. G. W., Venugopal, V. K., ... & Tan, M. O. (2024). An artificial intelligence boost to MRI lumbar spine reporting. European Journal of Radiology, 111636.
2. Syed Nasser, N., Venugopal, V. K., Veenstra, C., Johansson, P., Rajan, S., Mahajan, K., ... & Mahajan, H. (2024). Age-stratified Assessment of Brain Volumetric Segmentation on the Indian Population Using Quantitative Magnetic Resonance Imaging. Clinical Neuroradiology, 1-11.
3. Venugopal, V. K., Gupta, A., Takhar, R., & Mahajan, V. (2023). New Epochs in AI Supervision: Design and Implementation of an Autonomous Radiology AI Monitoring System. arXiv preprint arXiv:2311.14305.
4. Yan, Benjamin, Ruochen Liu, David E. Kuo, Subathra Adithan, Eduardo Pontes Reis, Stephen Kwak, Vasantha Kumar Venugopal et al. "Style-aware radiology report generation with radgraph and few-shot prompting." arXiv preprint arXiv:2310.17811 (2023).
5. Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Min Ho Lee, Zahra Shakeri Hossein Abad, Andrew Y. Ng, Curtis P. Langlotz, Vasantha Kumar Venugopal, Pranav Rajpurkar. "Evaluating progress in automatic chest x-ray radiology report generation." Patterns 4.9 (2023).
6. Venugopal, V. K., Gupta, A., Takhar, R., Yee, C. L. J., Jones, C., & Szarf, G. (2023). Navigating Fairness in Radiology AI: Concepts, Consequences, and Crucial Considerations. arXiv preprint arXiv:2306.01333.
7. Jimenez-Pastor, A., Lopez-Gonzalez, R., Fos-Guarinos, B. et al. Automated prostate multi-regional segmentation in magnetic resonance using fully convolutional neural networks. Eur Radiol (2023). https://doi.org/10.1007/s00330-023-09410-9
8. Kaviani, P.; Kalra, M.K.; Digumarthy, S.R.; Gupta, R.V.; Dasegowda, G.; Jagirdar, A.; Gupta, S.; Putha, P.; Mahajan, V.; Reddy, B.; Venugopal, V.K.; Tadepalli, M.; Bizzo, B.C.; Dreyer, K.J. Frequency of Missed Findings on Chest Radiographs (CXRs) in an International, Multicenter Study: Application of AI to Reduce Missed Findings. Diagnostics 2022, 12, 2382. https://doi.org/10.3390/diagnostics12102382
9. Mittal S, Venugopal VK, Agarwal VK, Malhotra M, Chatha JS, Kapur S, et al. (2022) A novel abnormality annotation database for COVID-19 affected frontal lung X-rays. PLoS ONE 17(10): e0271931. https://doi.org/10.1371/journal.pone.0271931
10. Venugopal, V.K., Takhar, R., Gupta, S. et al. Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – Changing the Way We Validate Classification Algorithms. J Med Syst 46, 20 (2022). https://doi.org/10.1007/s10916-022-01806-2
11. Amerta Ghosh, Koel Dutta, Surya Prakash Bhatt, Ritesh Gupta, Kanika Tyagi, Irshad Ahmad Ansari, Vasantha Kumar Venugopal, Harsh Mahajan, Ravindra Mohan Pandey, Shivam Pandey, Anoop Misra, Dapagliflozin Improves Body Fat Patterning, and Hepatic and Pancreatic Fat in Patients With Type 2 Diabetes in North India, The Journal of Clinical Endocrinology & Metabolism, Volume 107, Issue 6, June 2022, Pages e2267–e2275, https://doi.org/10.1210/clinem/dgac138
12. Jogi SP, Thaha R, Rajan S, Mahajan V, Venugopal, V. K., Singh A, Mehndiratta A. Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis. J Transl Med. 2021 Jul 19;19(1):310. doi: 10.1186/s12967-021-02977-1
13. Jogi SP, Thaha R, Rajan S, Mahajan V, Venugopal, V. K., Mehndiratta A, Singh A. Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging. J Magn Reson Imaging. 2021 Aug 9. doi: 10.1002/jmri.27877
14. Venugopal VK, Vaidhya K, Murugavel M, Chunduru A, Mahajan V, Vaidya S, Mahra D, Rangasai A, Mahajan H. Unboxing AI - Radiological Insights into a Deep Neural Network for Lung Nodule Characterization. Acad Radiol 27, 88–95 (2020).
15. Mahajan, V, Venugopal, V. K., Murugavel, M. & Mahajan, H. The Algorithmic Audit: Working with Vendors to Validate Radiology-AI Algorithms-How We Do It. Acad Radiol 27, 132–135 (2020).
16. Chilamkurthy S, Ghosh R, Tanamala S, Biviji M, Campeau NG, Venugopal VK, et al. Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study. Lancet. 2018 Oct 11;
17. Vasanthakumar Venugopal, Alex Daniel Prabhu, Ishrat Afshan, Mehvash Haider, Ekram Ullah. 2014. Initial Experiences with a New MRI Scoring System for Differentiating Advanced Femoral Osteonecrosis from Tubercular Arthritis. Orthopedics 37:11, e1014-e1020
18. Narang, N. C., Diwaker, P., Narang, S. & Venugopal, V. K. Low-Grade Central Osteosarcoma: Report of Two Unusual Morphologic Variants. Indian J Surg Oncol 9, 74–78 (2018).
19. Arora, V. K., Chopra, N., Singh, P., Venugopal, V. K. & Narang, S. Hydatid cyst of parotid: Report of unusual cytological findings extending the cytomorphological spectrum. Diagn. Cytopathol. 44, 770–773 (2016).
20. Venugopal V, Haider M. First case report of acute hemorrhagic leukoencephalitis following Plasmodium vivax infection. Indian J Med Microbiol. 2013 Jan;31(1):79–81.
21. Venugopal V, Puri SK, Kapoor AK, Upreti L. Gallstone abscess: some drops may end up costlier! Indian J Gastroenterol. 2012 Aug 2;
22. Wahab S, Ahmad I, Kumar V, Qaseem D. Solitary vertebral plasmacytoma causing compression fracture in a patient with multiple vertebral hemangiomas: a diagnosis easily missed!. Orthop Rev (Pavia). 2011 Dec;3(2):e15
23. Daniel A, Ullah E, Wahab S, Kumar V. Relevance of MRI in prediction of malignancy of musculoskeletal system-A prospective evaluation. BMC Musculoskelet Disord 2009;10(1):125.

1. RSNA 2024: AI-Assisted Lung Nodule Detection: Clinical and Economic Impact Beyond Cancer Screening Programs

2. RSNA 2024: Unraveling the Complexities of Elusive Fractures: A Synergistic AI-Radiologist Approach for Enhanced Detection

3. RSNA 2024: Contrasting Carbon Emissions of Two Machine Learning Training Approaches: From Scratch Versus Pretrained Models 

4. ECR 2023: Quality assessment compliance using a combination of deep learning, NLP, and limited human intervention - Feasibility for real-time institutional deployment

5. ECR 2023: Subjective Joint Space Overestimation on Knee X-rays - Exploring the feasibility of an AI-based quality control

6. ECR 2023: Clinical Outcome prediction in pediatric traumatic brain injuries using multiparametric artificial neural networks based on CT findings, GCS score, blood glucose, and Hb levels

7. ECR 2023: Predicting the projection information on Mammograms using Deep Learning - a potential AI input optimization plug-in?

8. ECR 2023: AI-enabled Multi-institutional Audit for prevalence of Missed Spondylolisthesis on Spine X-rays

9. ECR 2023: Classification of Central Venous Catheter using Deep Learning algorithm and its evaluation on an independent dataset with and without Test time Augmentation

10. ECR 2023: Automated CT severity score analysis of COVID19 pneumonia - A comparative analysis against radiologists' estimation during a pandemic surge

11. ECR 2023: 100% perfect classifier using AI ensembling: A novel deployment system that balances cost & efficiency

12. ECR 2023: Evaluating the effect of dataset drift during COVID pandemic on the performance of DL-based chest X-ray classification algorithm

13. ECR 2023: Initial Experience Using 3D quantitative Synthetic MRI in Estimation of Brain Tissue Volumes in Normal & Abnormal Cases

14. ECR 2023: Utilizing large-scale mammography data to establish normative breast density distribution relative to age in Indian population.

15. ECR 2023: Estimation of white matter hyperintensities with synthetic MRI myelin volume fraction in patients with multiple sclerosis and non-MS white matter hyperintensities

16. ECR 2023: Prospective evaluation of correlation between liver fat values estimated using a novel HepaFat-Scan PDFF and standard of care - IDEAL-IQ PDFF techniques:

17. ECR 2023: Evaluation of correlation between Brain Parenchymal Fraction estimated using a deep learning-based algorithm and synthetic MRI in healthy volunteers

18. ECR 2023: Orthostatic variation of the fourth ventricular volume & cerebellar tonsillar position on Open MR in normal healthy volunteers

19. ECR 2023: "Pediatric fMRI - A cheat sheet for the challenges!!"

20. ECR 2023: A Comparison of estimated post-processing time of two different DTI analysis methods for clinical research in a pediatric population

21. ECR 2023: The Many Faces of ROC Curves - Understanding the different types of ROC curves and their appropriate applications

22. ECR 2023: Things to Measure, Monitor and Document: Post Market Surveillance of AI Model

23. RSNA 2022: Evaluation of Operational Efficiency of Multisite Multi-modal Platform-Based Deployment of Multiple AI Solutions

24. ECR 2022: Why standardization of pre-inferencing image processing methods is crucial for deep learning algorithms: compelling evidence based on the variations in outputs for different inferencing workflows

25. RSNA 2021: Utility of Explainability failure Ratio in a high sensitivity screening setting to compare incorrect localizations among algorithms.

26. ECR 2021: How much does non-blinded assessment shift the goalpost for AI algorithms? Exploring the hidden role of bias in AI evaluation using knee osteoarthritis grading as an example.

27. ECR 2021: MR prevalence of incidental findings on brain MR: a retrospective analysis of 36,808 MRI scans.

28. ECR 2021: Qualitative and quantitative comparison of image quality of up-resolved simulated fast MR acquisitions and standard of care images.

29. RSNA 2020: Estimating AI-generated Bias in Radiology Reporting by Measuring the Change in the Kellgren-Lawrence Grades of Knee Arthritis Before and After Knowledge of AI Results—A Multi-reader Retrospective Study.

30. RSNA 2020: Assessment of Brain Tissue Microstructure by Diffusion Tensor Distribution MRI: An Initial Survey of Various Pathologies.

31. RSNA 2019: Can AI Generate Clinically Appropriate X-Ray

Reports? Judging the Accuracy and Clinical Validity of Deep Learning-Generated Test Reports as Compared to Reports Generated by Radiologists: A Retrospective Comparative Study.

32. RSNA 2019: Establishing Normative Kidney Sizes for a Large Developing Country's Adult Population Using Big Data: A Study of 30,000 Ultrasound Scans Yields a Potential Gender and Age-Related Difference.

33. RSNA 2019: Deploying Deep Learning for Quality Control: An AI-assisted Review of Chest X-Rays Reported as 'Normal' in Routine Clinical Practice

34. RSNA 2019: Evaluating the Complimentary Role of Pseudo-STIR in Assessment of Hyperintense Marrow Lesions as Compared to T2-STIR.

35. RSNA 2019: Making Spine MR Reports More Clinically Appropriate: A Questionnaire-Based Survey of Sub-Specialty Spine Surgeons.

36. RSNA 2019: Getting AI Ready for Deployment: Tuning Algorithms to Specific Sites Using a Single Chest X-Ray Image.

37. RSNA 2018: Hepatic Shear Wave Elastography: Correlation Between Liver Stiffness and Esophagogastric Varices.

38. RSNA 2018: Improving the Accuracy of Deep Learning Networks for Bone-Age Estimation by Incorporating Radiological Insight Guided Feature Analysis.

39. RSNA 2018: Acceleration of MR Imaging of Spine Using Compressed-SENSE: A Comparison with Existing Standard of Care Clinical Acquisition Methods.

40. RSNA 2018: T2 Nerve Imaging of the Brachial Plexus Using Compressed-SENSE Effect on Image Quality and Acquisition Time.

41. RSNA 2018: Evaluating Variability in Knee CartiGram MRI – A Quantitative Study.

42. RSNA 2018: Synthetic PET Generator: A Novel Method to Improve Lung Nodule Detection by Combining Outputs from a Pix2pix Conditional Adversarial Network and a Convolutional Neural Network Based Malignancy Probability Estimator.

43. RSNA 2011: Quantitative Elastographic Assessment of Nonpalpable Breast Nodules by Measuring Fat-Lesion Strain Ratio vs Qualitative Colour Elastography Scores: Comparison of Diagnostic Performances by a Blinded Prospective Study.

44. ECR 2011: An indigenous MRI scoring system for differentiating advanced femoral osteonecrosis from tubercular arthritis: myth or mystique?

45. RSNA 2010: Hippocampal T2 Relaxometry versus 1H MR Spectroscopy: Comparison of Lateralising Ability in Temporal Lobe Sclerosis.

46. ECR 2010: GI-RADS - gynecologic imaging reporting and data system: A standardized reporting system for adnexal masses.

47. IRIA 2010: Prediction of fetal anemia by assessment of Fetal Middle Cerebral Artery - Peak Systolic Velocity (MCA-PSV)