Abhi Jain

I’m a neuroradiologist at Stanford and a certified imaging informatics professional. I work where the reading room meets the systems around it: quantitative imaging in cerebrovascular disease, AI that has to earn its place in clinical workflow, and better ways to teach people to read.

The long way in: how bodies move, then how they heal, then how the brain looks from the inside.

1. 2011Master of Education, Exercise ScienceCleveland State University
2. 2015Doctor of Physical TherapyArizona School of Health Sciences
3. 2019Doctor of Osteopathic MedicinePhiladelphia College of Osteopathic Medicine
4. 2020Surgical internshipUniversity of Washington
5. 2024Diagnostic radiology residencyEinstein Medical Center Philadelphia
6. 2024Imaging informatics fellowshipUniversity of Pennsylvania
7. 2025Neuroradiology fellowshipUniversity of Southern California
8. NowClinical Assistant Professor of RadiologyStanford University. Member, Wu Tsai Neurosciences Institute. Editorial board, Clinical Neuroimaging.

Vessels.Carotid plaque and vessel wall imaging across MRI, CT angiography and ultrasound, and where automated plaque quantification changes what we can measure.

Hemorrhage.Radiomic and shape markers on admission CT that predict hematoma expansion and outcome in intracerebral hemorrhage, tested in multicenter trial cohorts.

Aging brain.Imaging biomarkers of neurodegeneration, including limbic-predominant age-related TDP-43 encephalopathy (LATE).

Reporting.Language models for report drafting and clinical decision support, judged by real-world evaluation and how well they fit the workflow.

Teaching.Tailored language models and extended reality for neuroradiology trainees.

Prior studies, selected. The complete record is on ORCID.

1. 2023Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markersFrontiers in Neuroscience
2. 2022The coronal plane maximum diameter of deep intracerebral hemorrhage predicts functional outcome more accurately than hematoma volumeInternational Journal of Stroke
3. 2022Brain tumor imaging: applications of artificial intelligenceSeminars in Ultrasound, CT and MRI
4. 2021Admission computed tomography radiomic signatures outperform hematoma volume in predicting baseline clinical severity and functional outcome in the ATACH-2 trial intracerebral hemorrhage populationEuropean Journal of Neurology
5. 2021Imaging of spontaneous intracerebral hemorrhageNeuroimaging Clinics of North America
6. 2021P2Y12 inhibitors in neuroendovascular surgery: an opportunity for precision medicineInterventional Neuroradiology
7. 2021Impact of telerehabilitation for stroke-related deficitsTelemedicine and e-Health
8. 2020Poor outcomes related to anterior extension of large hemispheric infarction: topographic analysis of GAMES-RP trial MRI scansJournal of Stroke and Cerebrovascular Diseases
9. 2019Comparison of Pipeline Embolization Device and Flow Re-Direction Endoluminal Device flow diverters for internal carotid artery aneurysms: a propensity score-matched cohort studyNeurosurgery
10. 2019Proposal of a follow-up imaging strategy following Pipeline flow diversion treatment of intracranial aneurysmsJournal of Neurosurgery
11. 2019Predictive factors of incomplete aneurysm occlusion after endovascular treatment with the Pipeline embolization deviceJournal of Neurosurgery
12. 2019Pharmacy-mediated antiplatelet management protocol compared to one-time platelet function testing prior to Pipeline embolization of cerebral aneurysms: a propensity score-matched cohort studyNeurosurgery
13. 2019Evaluation of radiological features of the posterior communicating artery and their impact on efficacy of saccular aneurysm treatment with the Pipeline Embolization Device: a case series studyWorld Neurosurgery
14. 2019A case of post-angiography subdural collection contrast enhancement: time course of attenuation reductionRadiology Case Reports
15. 2018Neuroprotection in traumatic brain injuryJournal of Neurosurgical Sciences

Ceramics, 3D printing, and making music on a Teenage Engineering EP-133. Probably significant. Follow-up recommended.

1. Neuroradiologist and imaging informaticist at Stanford.
2. Quantitative imaging and clinical AI, evaluated where it counts: in real use.
3. Open to collaborations, invited talks, and good conversations about any of the above.

Correlation by email recommended: hello@abhijain.com

WNRS 2026.AI plaque quantification in carotid disease, at the Western Neuroradiological Society annual meeting. The argument: AI’s contribution isn’t out-reading an experienced radiologist. It’s reach, consistency, and measurements no one can make by eye.