Yashvardhan Jain
Computer Science · Indiana University
Publications
41
Citations
499
Est. group size
~2
Recurring co-author estimate
Active years
12
Publishing since 2015
Yashvardhan Jain works in computer science applied to biomedical imaging, developing deep learning methods to automatically identify structures in medical scans. A recent focus is 3D segmentation of blood vessels in high-resolution tissue images, such as kidney scans obtained through phase contrast tomography. This work sits at the intersection of artificial intelligence, cell and tissue image analysis, and medical imaging.
Publication activity was sparse until around 2021, then rose sharply from 2023 onward, indicating a period of growing output in recent years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Deep learning for 3D vascular segmentation in hierarchical phase contrast tomography: a case study on kidney
Scientific Reports · 2024
- Deep Learning for 3D Vascular Segmentation in Phase Contrast Tomography
SSRN Electronic Journal · 2024
- Deep Learning for 3D Vascular Segmentation in Phase Contrast Tomography
Research Square · 2024
- Deep Learning for Vascular Segmentation and Applications in Phase Contrast Tomography Imaging
arXiv (Cornell University) · 2023
- Trained Model Weights for the Multiftu Segmentation Pipeline
Zenodo (CERN European Organization for Nuclear Research) · 2023
- Trained Model Weights for the Multiftu Segmentation Pipeline
Zenodo (CERN European Organization for Nuclear Research) · 2023
- Manual Segmentation of Tissue
Open MIND · 2022
- Predicting parole hearing result using machine learning
2017
- Zenodo (CERN European Organization for Nuclear Research)×16
- bioRxiv (Cold Spring Harbor Laboratory)×7
- Nature Communications×2
- Kidney International×1
- Nature Methods×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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