About Us

Developing AI solutions for healthcare that solve real clinical challenges.

Keya Medical is a medical technology company developing AI applications that enable healthcare delivery organizations to provide better patient care. Our data scientists, software engineers, and designers collaborate with medical centers around the world to apply the latest advances in deep learning, computer vision, and medical image analysis to improve human health.

Since 2016, we have been applying our AI expertise to some of the most challenging problems in healthcare. Before starting the company, many of our team members worked together for over ten years developing advanced technologies for leading medical technology manufacturers.

Keya Medical is committed to developing solutions that solve real clinical challenges. Our team works with in-house clinicians and external advisers who help us navigate the clinical workflow and define clinical use cases. Over the past five years, we have partnered with over 200 healthcare systems worldwide, and our products have been adopted throughout hospitals in Asia.

Milestones

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2020

December 2020
 – Keya Medical raises $46 million in Series D funding

November 2020
 –
Keya Medical closes $30 million in Series C funding

September 2020
 – Keya Medical is awarded China’s Most Promising Company Award by Ernst & Young Fudan China
 – CuraRad-ICH joins Nuance AI Marketplace for Diagnostic Imaging

August 2020
 –
Keya Medical closes $20 million in Series B+ funding

March 2020
 –
CuraRad-ICH receives U.S. FDA 510(k) clearance

February 2020
 –
Keya Medical raises over $15 million in strategic funding

January 2020
 –
DeepVessel FFR becomes the first Class-III AI medical device approved for clinical use by the Chinese National Medical Products Administration

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2019

December 2019
 –
Keya Medical is selected to the Top 100 Medical Companies of the Future list by VCBeat Research

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2018

August 2018
 –
DeepVessel FFR receives CE certification

June 2018
 –
Keya Medical receives ISO 13485 certification

April 2018
 –
DeepVessel FFR enters the CFDA Special Approval Channel for Innovative Medical Devices

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2017

October 2017
 –
Keya Medical establishes the first AI diagnostic laboratory in China

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2016

January 2016
 –
Keya Medical is founded

Recent Publications

Additional Value of Deep Learning Computed Tomographic Angiography-based Fractional Flow Reserve in Detecting Coronary Stenosis and Predicting Outcomes
Li, Y., Qiu, H., Hou, Z., et al.
Acta Radiologica, 2021.

Simultaneous Classification and Segmentation of Intracranial Hemorrhage Using a Fully Convolutional Neural Network
Guo, D., Wei, H., Zhao, P., Pan, Y, et al.
International Symposium on Biomedical Imaging (ISBI), IEEE, April 2020.

Artificial Intelligence Distinguishes COVID-19 from Community Acquired Pneumonia on Chest CT
Li L., Qin L., Xu Z. Yin, Y., Wang, X., et al.
Radiology, March 2020.

All Publications

Additional Value of Deep Learning Computed Tomographic Angiography-based Fractional Flow Reserve in Detecting Coronary Stenosis and Predicting Outcomes
Li, Y., Qiu, H., Hou, Z., et al.
Acta Radiologica, 2021.

Simultaneous Classification and Segmentation of Intracranial Hemorrhage Using a Fully Convolutional Neural Network
Guo, D., Wei, H., Zhao, P., Pan, Y, et al.
International Symposium on Biomedical Imaging (ISBI), IEEE, April 2020.

Artificial Intelligence Distinguishes COVID-19 from Community Acquired Pneumonia on Chest CT
Li L., Qin L., Xu Z. Yin, Y., Wang, X., et al.
Radiology, March 2020.
Learning Physical Properties in Complex Visual Scenes: An Intelligent Machine for Perceiving Blood Flow Dynamics from Static CT Angiography Imaging
Gao Z., Wang, X., Sun, S., Wu, D., Bai, J., Yin, Y., et al.
Neural Networks, 2020.

Learning Tree-structured Representation for 3D Coronary Artery Segmentation
Kong, B., Wang, X., Bai, J., Lu, Y., Gao, F., Cao, K., et al.
Computerized Medical Imaging and Graphics, 2020.

DeepCenterline: A Multi-task Fully Convolutional Network for Centerline Extraction
Guo Z., Bai, J., Lu, Y., Wang X., Cao K., et al.,
International Conference on Information Processing in Medical Imaging (IPMI), 2019.

Residual Attention Based Network for Hand Bone Age Assessment
Wu E, Kong B, Wang X, Bai J, Lu Y, et al.,
IEEE International Symposium on Biomedical Imaging (ISBI), 2019.

Dual Adversarial Auto-encoder for Dermoscopic Image Generative Modeling
Yang, HY, Staib, L.,
IEEE International Symposium on Biomedical Imaging (ISBI), 2019.

Evaluation of Fractional Flow Reserve in Patients with Stable Angina: Can CT Compete with Angiography?
Liu, X., Wang, Y., Zhang, H., Yin, Y., Cao, K., et al.
European Radiology, 2019.

Automated Anatomical Labeling of Coronary Arteries via Bidirectional Tree LSTMs
Wu, D., Wang, X., Bai, J., Xu, X., Ouyang B., et al.
International Journal of Computer Assisted Radiology and Surgery, 2019.14: 271.

Automatic Brain Tumor Segmentation with Contour Aware Residual Network and Adversarial Training
Yang, HY. Yang, J.,
International MICCAI Brain Lesion Workshop, 2018.

Volumetric Adversarial Training for Ischemic Stroke Lesion Segmentation
Yang, HY.
International MICCAI Brain Lesion Workshop, 2018.

Learn to be Uncertain: Leveraging Uncertain Labels in Chest X-Rays with Bayesian Neural Networks
Yang HY, Yang J, Pan Y, Cao K, Song Q, et al., Uncertainty and Robustness in Deep Visual Learning Workshop, IEEE Conference on Computer Vision and Pattern Recognition, June, 2019.

Precise Diagnosis of Intracranial Hemorrhage and Subtypes Using a Three-dimensional Joint Convolutional and Recurrent Neural Network
Ye H*, Gao F* (*Equal contribution), Yin Y, Guo D, Zhao P, et al., European Radiology, March, 2019.

Diagnostic Accuracy of a Deep Learning Approach to Calculate FFR from Coronary CT Angiography
LWang, Z., Zhou, Y., Zhao, Y., Shi, D., Liu, Y., et al.
Journal of Geriatric Cardiology, 2019.

Train a 3D U-Net to Segment Cranial Vasculature in CTA Volume without Manual Annotation
Chen, X., Lu, Y., Bai, J., et al.
IEEE 15th International Symposium on Biomedical Imaging (ISBI), 2018.

Invasive Cancer Detection Utilizing Compressed Convolutional Neural Network and Transfer Learning
Kong, B., Sun, S., Wang, X., et al.
In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018.

A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography
Kirby M, Yin Y, et al.,
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018.

Integrate Domain Knowledge in Training CNN for Ultrasonography Breast Cancer Diagnosis
Liu, J., Li, W., Zhao, N., Cao, K., Yin Y., et al.
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018.

Train a 3D U-Net to Segment Cranial Vasculature in CTA Volume without Manual Annotation
Chen X, Lu Y, Bai J, Yin Y, Cao K, Li Y, et al.,
International Symposium on Biomedical Imaging (ISBI), 2018.

Hemodynamics Analysis of the Serial Stenotic Coronary Arteries
Liu, X., Peng, C., Xia, Y., et al.
Biomedical Engineering Online.16(1).127, 2017.

A Study of Noninvasive Fractional Flow Reserve Derived from a Simplified Method based on Coronary Computed Tomography Angiography in Suspected Coronary Artery Disease
Shi, C., Zhang, D., Cao, K., et al.
Biomedical Engineering Online.16(1).43, 2017.

Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning
Hussein, S., Cao, K., Song, Q., et al.
International Conference on Information Processing in Medical Imaging (IPMI), 2017.

Cancer Metastasis Detection via Spatially Structured Deep Network
Kong B*, Wang X* (*Equal contribution), Li Z, Song Q, Zhang S.
International Conference on Information Processing in Medical Imaging (IPMI), 2017.

TumorNet: Lung Nodule Characterization using Multi-view Convolutional Neural Network with Gaussian Process
Hussein, R. Gillies, K. Cao, et al.
IEEE 14th International Symposium on Biomedical Imaging (ISBI), 2017.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method
Guo X, Dominick K, Minai, A, Li H, Erickson C, et al.,
Frontiers in Neuroscience, 11, 460. 2017.

A Computational Model for the Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Based on Functional Brain Volume
Tan L, Guo X, Ren S, Epstein, J, Lu L
Frontiers in Computational Neuroscience, 11, 75. 2017.

Towards Quantitative Assessment of Rheumatoid Arthritis Using Volumetric Ultrasound
Cao K, Mills DM, Thiele RG, Patwardhan KA
IEEE Transactions on Biomedical Engineering (TBME), 63(2): 449-458, 2016.

MASCG: Multi-Atlas Segmentation Constrained Graph Method for Accurate Segmentation of Hip CT image
Chu C, Bai J, Wu X, Zheng G.
Medical Image Analysis, 26(1):173, December 2015.

Multiple Surface Segmentation Using Truncated Convex Priors
Shah A, Bai J, Hu Z, Sadda S, Wu X
Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015.

Computed Tomography Predictors of Response to Endobronchial Valve Lung Reduction Treatment. Comparison with Chartis
Schuhmann M, RaffyP, Yin Y, Gompelmann D, Oguz I et al.,
American Journal of Respiratory and Critical Care Medicine (AJRCCM), Vol. 191 (7), 767-774, 2015.

Error-tolerant Scribbles Based Interactive Image Segmentation
Bai J, Wu X
Computer Vision and Pattern Recognition (CVPR), 2014 .

Globally Optimal Lung Tumor Co-segmentation of 4D CT and PET Images
Bai J, Song Q, Bhatia S, Wu X
Proceedings of SPIE Medical Imaging (oral presentation), 2013.

Optimal Co-segmentation of Tumor in PET-CT Images with Context Informations
Song Q,  Bai J, Han D, Bhatia S, Sun W, et al.,
IEEE Transactions on Medical Imaging, 32(9):1685-97, September 2013.

Intensity-based Registration for Lung Motion Estimation
Cao K, Ding K, Amelon R, Du K, Reinhardt J et al.,
In Springer Book on “4D Modeling and Estimation of Respiratory Motion for Radiation Therapy”, published in the Springer series Biological and Medical Physics, Biomedical Engineering 2013, pp 125-158.

Motion-Compensated Mega-Voltage Cone Beam CT Using the Deformation Derived Directly from 2D Projection Images
Chen M, Cao K,  Zheng Y, Siochi R
IEEE Transactions on Medical Imaging, 32(8): 1365-1375, 2013.

Fast Dynamic Programming for Labeling Problems with Ordering Constraints
Bai J, Song Q, Veksler O, Wu X
Computer Vision and Pattern Recognition (CVPR), 2012.

Registration-based Estimates of Local Lung Tissue Expansion Compared to Xenon CT Measures of Specific Ventilation
Reinhardt J, Ding K, Cao K, Christensen G, Hoffman E, et al.,
Medical Image Analysis, 12(6):752-763, 2008 .