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About Vetology Ai
Ai refers to Artifical intelligence or Augmented interpretation. This is the radiograph interpretation resource veterinarians have been looking for. This online resource is Worldwide.

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    See for yourself how easy it is to bring Vetology Ai into your practice. Monthly & yearly subscription options are available under pricing. Not sure? See the demo under Try Ai or watch this video.

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      Meet Vetology's AI Advisory Board

        Dr. Albert Hsiao UCSD Radiology

        Staff Rank:

        Assistant Professor of Radiology


        Albert Hsiao, UCSD Radiology


        Radiology, Bioinformatics


        • Co-founded Arterys, Inc, (~$46 million in funding) developed a cloud-based medical imaging artificial intelligence platform and partnered with GE Healthcare.
        • Founded the Augmented imaging/Artificial intelligence Data Analytics (AiDA) laboratory to further build advanced imaging techniques for earlier, more precise diagnosis and treatment in cardiovascular disease and oncology.
        • Stanford general surgery, diagnostic radiology, interventional radiology and cardiovascular imaging.
        • Dual-degree MD-PhD Medical Scientist Training Program (MSTP). He is a graduate of the UCSD Bioengineering and Bioinformatics PhD programs.
        • Dual-major at Caltech in Biology and Engineering/Computer Science.

        In The News:

        Selected Publications:

        • 4D flow MRI quantification of mitral and tricuspid regurgitation: Reproducibility and consistency relative to conventional MRI.. J Magn Reson Imaging. 2018 Apr 11. View in: PubMed
        • Volumetric segmentation-free method for rapid visualization of vascular wall shear stress using 4D flow MRI.. Magn Reson Med. 2018 Mar 07. View in: PubMed
        • Pelvic Blood Flow Predicts Fibroid Volume and Embolic Required for Uterine Fibroid Embolization: A Pilot Study With 4D Flow MR Angiography.. AJR Am J Roentgenol. 2017 Nov 01; 1-12. View in: PubMed
        • Improved quantification and mapping of anomalous pulmonary venous flow with four-dimensional phase-contrast MRI and interactive streamline rendering.. J Magn Reson Imaging. 2015 Dec; 42(6):1765-76. View in: PubMed
        Jayashree Kalpathy-Cramer, PhD

        Staff Rank:

        • Director of the QTIM lab
        • Director of the Center for Machine Learning at the Athinoula A. Martinos Center for Biomedical Imaging
        • Associate Professor of Radiology at MGH/Harvard Medical School


        • QTIM lab
        • Center for Machine Learning at the Athinoula A. Martinos Center for Biomedical Imaging
        • MGH/Harvard Medical School


        • Medical image analysis
        • Machine learning and artificial intelligence for applications in radiology
        • Oncology and ophthalmology


        • B.Tech in Electrical Engineering from IIT, Bombay, India
        • MS and PhD in Electrical Engineering from Rensselaer Polytechnic Institute
        • MS in Biomedical Informatics from Oregon Health and Science University
        Recently, her lab has been actively working in the applications of deep learning to clinical problems in ophthalmology, oncology and radiology. She has authored over a 100 peer-reviewed publications and over 10 book chapters.