OrthoPred applies artificial intelligence, particularly state of the art deep and machine learning tools to analyze orthopedic medical data and images, to assist radiologists in making diagnoses as fast and accurate as possible.
Our solutions are available as an API, and are currently validated by Iconomix Ltd., one of the largest Central European teleradiology provider.
Our deep learning algorithm is able to classify the severity of knee and hip osteoarthritis according to Kellgren-Lawrence grade based on knee X-ray images.
Our deep learning algorithm can detect meniscal tears in 2D and 3D knee MRI scans.
Deep learning, and particularly convolutional neural networks have revolutionalized the field of image processing. These new tools can be adapted to medical imaging to aid radiologists in accurate and objective diagnosis.
Co-founders & Experience
Our interdisciplinary team shares unique knowledge of healthcare, computer science, higher mathematics and engineering. With our diverse background we can tackle the challenges of applying deep learning for medical imaging.
Dr Andor Viktor Gál, MD, PhD CEO: Musculoskeletal radiologist with PhD in bioinformatics, MRI sequence programming license, substantial experience in neural network implementation, medical image processing. Role: Creating and forming the strategy of the provided service. Coordination of development in the fields of data (pre)processing and filtering.
Regina Meszlényi, PhD, CTO: Machine learning researcher with background in theoretical and medical physics. Experience in imaging software development in corporate environment at Mediso Medical Imaging Systems Ltd. Role: coordination of development of machine learning algorithms and deep learning architecture.
Iconomix Ltd. Our current validation partner is one of the largest teleradiology provider in central Europe. For testing and validation purposes, we seek collaboration with medical institutes, who are interested in our deep learning solutions. Contact us at: email@example.com