The Bioinformatics and Computational Biosciences Branch's (BCBB) imaging team aims to understand the structure and distribution of components and processes at the sub-cellular, cellular, or gross anatomical levels. Areas of collaboration include:
- Image classification and segmentation (deep learning).
- Image registration.
- Workflow development.
Areas of Expertise
- AI for image analysis.
- Microscopy and clinical image analysis.
- Data sharing.
Technologies
Publications
Collaborator: Ronald Germain (LISB). IBEX: an iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues. Nat Protoc, 2022. 17(2): 378-401.
Collaborator: Ronald Germain (LISB). IBEX: A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues. Proc. Natl. Acad. Sci. USA. 2020.
Collaborator: Stefan Jaeger (NLM). Generalization Challenges in Drug-Resistant Tuberculosis Detection from Chest X-rays. Diagnostics 12(1). 2022.
Collaborator: Stefan Jaeger (NLM). Differentiating between drug-sensitive and drug-resistant tuberculosis with machine learning for clinical and radiological features. Quant Imaging Med Surg. 2022. Surg, 12(1): 675-687.
Research Team
Team Lead
Ziv Yaniv, Ph.D.
(Contractor)
Education:
Ph.D., 2004, The Hebrew University of Jerusalem, Jerusalem, Israel
Languages Spoken: Hebrew
Ziv Yaniv is a senior imaging scientist. His expertise is in image-guided surgical interventions and bio-medical image analysis. He believes in the curative power of open research and has been involved in development and leadership of free open source software, including the Image-Guided Surgery Toolkit, the Insight Registration and Segmentation Toolkit and SimpleITK.
Team Members
David T. Chen, Ph.D.
(Contractor)
Education:
B.A., 1988, University of California, Berkeley, Berkeley, CA
M.S., 1991, University of North Carolina at Chapel Hill, Chapel Hill, NC
Ph.D., 1998, University of North Carolina at Chapel Hill, Chapel Hill, NC
David Chen is a senior visualization scientist. His background is in interactive 3D computer graphics and 3D medical image analysis. He is a core developer of the SimpleITK software toolkit for medical image segmentation and registration.
Karthik Kantipudi, M.S.
(Contractor)
Education:
B.S., Indian Institute of Technology Kharagpur, West Bengal, India
M.S., University of St. Thomas, St Paul, MN
Languages Spoken: Hindi, Telugu
Karthik Kantipudi is an imaging specialist working primarily with the NIAID TB Portals Program. He received his master's degree in data science from the University of St. Thomas and a Bachelor's degree from IIT Kharagpur. At Bioinformatics and Computational Bioscience Branch (BCBB), he conducts research in deep learning and machine learning involving medical images and clinical information.
