Our Services
Full-Stack Medical AI Development
From data pre-processing and visualization to hyper-parameter optimization for medical device companies.
From building webapps and notebooks, to cloud gpu training and boosted decision tree algorithm development.
We do it all.
- We assist healthcare customers in developing AI solutions, including classification, regression, 2D & 3D segmentation, 2D & 3D co-registration, hyperparameter optimization, neural network architecture design.
- We develop live AI dashboards and webapps for use in clinical studies.
- We build serverless cloud infrastructure (using modern IAC approaches) for model training and data pipelines.
- We help containerize environments, and convert algorithms or Matlab / C++ code into Python.
- Experience with popular open source medical AI libraries and tools including MONAI, OHIF, ITK, VTK, 3DSLICER, SCIKIT, SciPy, PyPPG, TSAI
- We have experience in 3D & 4D medical imaging formats including: DICOM, DICOM-SEG, DICOM-RT, OpenSlide, NRRD, NIFTI, MHA
Build smarter, more efficient healthcare algorithms with AI-driven insights and data science expertise.
Sub-services:
- Medical Image Analysis and Segmentation – Advanced AI solutions for precise analysis of medical imaging data.
- 2D and 3D Segmentation – Accurate AI-driven segmentation of medical images for improved diagnostics and targeted treatments.
- 2D and 3D Coregistration Algorithms – Precise alignment of multimodal medical images, enabling comprehensive clinical assessments.
- Object Detection – Automated identification and localization of clinically significant structures or anomalies within medical imaging.
- Image Classification – AI-powered categorization of medical images to streamline clinical decision-making and enhance diagnostic accuracy.
- Volumetric Rendering – Advanced 3D visualization of medical imaging data, enabling intuitive exploration and clinical decision-making.
Case Studies
Real-World Impact
Explore our successful healthcare AI case studies.
Algorithm for Collaboration & Distribution
Updating disparate and unorganized AI algorithm code into cohesive and easily sharable notebooks.
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Clinical UI Design for Radiology AI
Creating intuitive software interfaces that empower doctors and accelerate AI innovation
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Developing 3D Radiology AI Solutions
Moving University Client to the Cloud with Open Source Medical AI Models
Read MorePublications
Explore Our Work
See our 35+ Peer-Reviewed Publications & Patents.
Improved Active Shape Models for Segmentation of the Prostate on MR Imagery
Toth, R. “Improved Active Shape Models for Segmentation of the Prostate on MR Imagery,” M.S. Thesis, Rutgers University, 2010.
Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge
Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., Vincent, G., Guillard, G., Birbeck, N., Zhang, J., Strand, R., Malmberg, F., Ou, Y., Davatzikos, C., Kirschner, M., Jung, F., Yuan, J., Qiu, W., Gao, Q., Edwards, P.E., Maan, B., van der Heijden, F., Ghose, S., Mitra, J., Dowling, J., Barratt, D., Huisman, H., Madabhushi, A. “Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge.” Medical Image Analysis 25:18(2), Dec 2013 pp. 359-373. doi: 10.1016/j.media.2013.12.002
HistostitcherTM: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework
Toth, R.J., Shih, N., Tomaszewski, J.E., Feldman, M.D., Kutter, O., Yu, D.N., Paulus, J.C., Paladini, G., Madabhushi, A., “HistostitcherTM: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework.” Journal of Pathology Informatics 5(8), Mar 2014. doi: 10.4103/2153-3539.129441
A Domain Constrained Deformable (DoCD) Model for Co-registration of Pre- and Post-Radiated Prostate MRI
Toth, R., Traughber, B., Ellis, R., Kurhanewicz, J., Madabhushi, A., “A Domain Constrained Deformable (DoCD) Model for Co-registration of Pre- and Post-Radiated Prostate MRI.” Neurocomputing 144(20) Nov 2014. pp. 3-12 doi: 10.1016/j.neucom.2014.01.058
Professor Anant Madabhushi
Executive Director for the Emory Empathetic AI for Health Institute
Assistant Professor Andrew Janowczyk
Emory University
Mike Galvin
Co-Founder & Chairman of LivAI
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