PACS Quantitative Analysis Workbench
Advanced intelligent data integration and analysis capabilities help improve clinical efficiency and treatment results
NMPA class II certificate approved
Wukong Image Acquisition Workbench
Our portable medical device offers radiation-free 3D light analysis of the body, allowing for accurate assessment of spinal morphology
4D Brace service
Intelligent orthotic design with personalized adjustments targeting the progression of spinal deformity and mechanical optimization
NMPA class I certificate approved
AlignPro Expert Studio
Provide users with convenient, efficient, and personalized musculoskeletal traininig and disease management solutions
About Us
CoNova Medical Technology
CoNova Medical Technology is a provider of digital medical health management solutions, founded by researchers and engineers of the Digital Health Laboratory at the University of Hong Kong's Faculty of Medicine. The team consists of clinical surgeons from the same Faculty, as well as AI scientists and engineers from the Department of Computer Science at the University of Cambridge and Silicon Valley.CoNova Medical Technology is committed to evidence-based medicine and digital innovation, enabling high-level intelligent orthopedic diagnosis and treatment services. The company aims to enhance the 'intelligent ability' of medical staff, improve the 'intelligent service' for patients, and optimize the 'intelligent management' for medical institutions, all in an effort to support the department's transition towards building intelligent orthopedics.
Intelligent Management
Intelligent Service
Intelligent Ability
About Us
CoNova Medical Technology
CoNova Medical Technology is a provider of digital medical health management solutions, founded by researchers and engineers of the Digital Health Laboratory at the University of Hong Kong's Faculty of Medicine. The team consists of clinical surgeons from the same Faculty, as well as AI scientists and engineers from the Department of Computer Science at the University of Cambridge and Silicon Valley.CoNova Medical Technology is committed to evidence-based medicine and digital innovation, enabling high-level intelligent orthopedic diagnosis and treatment services. The company aims to enhance the 'intelligent ability' of medical staff, improve the 'intelligent service' for patients, and optimize the 'intelligent management' for medical institutions, all in an effort to support the department's transition towards building intelligent orthopedics.Intelligent Management
Intelligent Service
Intelligent Ability
PACS Quantitative Analysis Workbench
Wukong Image Acquisition Workbench
AlignPro Expert Studio
4D Brace service
PACS Quantitative Analysis WorkbenchWukong Image Acquisition WorkbenchAlignPro Expert Studio4D Brace serviceResearch Projects
Medical Image Registration And Naviagtion
In this project, we aim to investigate and develop novel image registration techniques for medical imaging analysis. We explore different registration methods, including intensity-based, feature-based, and learning-based, and evaluate their performance on various medical imaging modalities, such as CT, MR, optical imagery etc.
Orthopaedic Biomechanics and Implant Design
We have demonstrated that trabecular microarchitecture (TraMicroArcht) can vary the apparent modulus (E), yield strength of trabecular bone accurately. Micro-finite element analysis can quantify the effects of TraMicroArcht on mechanical properties. MicroCT images can be converted directly into digital models via our in-house developed new system and simulate virtual loading effects. Our new system can also have significant application in fast implant design and optimization.
3D Quantitative Analysis & Surgical Planning
We have developed an AI-driven pipeline for the quantitative analysis of the spine. We have established an unsupervised deep learning framework called MRI-SegFlow for the segmentation of multiple spinal tissues in spinal MRI, which achieved comparable performance with the state-of-art supervised methods and without relying on any manually masked ground truth.
Multi-View Mark-Less Surgical Navigation System
Advancements in spinal surgery have been made with the use of screw-based fixation devices. To enhance the precision of interventions such as screw insertion, we would propose a multi-view mark-less surgical navigation system. This system provides real-time tracking of surgical instruments and accurate registration of preoperative CT images. The benefits include improved accuracy, reduced invasiveness, decreased radiation exposure, and potentially more effective procedures.
Research Projects
Medical Image Registration And Naviagtion
In this project, we aim to investigate and develop novel image registration techniques for medical imaging analysis. We explore different registration methods, including intensity-based, feature-based, and learning-based, and evaluate their performance on various medical imaging modalities, such as CT, MR, optical imagery etc.
Orthopaedic Biomechanics and Implant Design
We have demonstrated that trabecular microarchitecture (TraMicroArcht) can vary the apparent modulus (E), yield strength of trabecular bone accurately. Micro-finite element analysis can quantify the effects of TraMicroArcht on mechanical properties. MicroCT images can be converted directly into digital models via our in-house developed new system and simulate virtual loading effects. Our new system can also have significant application in fast implant design and optimization.
3D Quantitative Analysis & Surgical Planning
We have developed an AI-driven pipeline for the quantitative analysis of the spine. We have established an unsupervised deep learning framework called MRI-SegFlow for the segmentation of multiple spinal tissues in spinal MRI, which achieved comparable performance with the state-of-art supervised methods and without relying on any manually masked ground truth.
Multi-View Mark-Less Surgical Navigation System
Advancements in spinal surgery have been made with the use of screw-based fixation devices. To enhance the precision of interventions such as screw insertion, we would propose a multi-view mark-less surgical navigation system. This system provides real-time tracking of surgical instruments and accurate registration of preoperative CT images. The benefits include improved accuracy, reduced invasiveness, decreased radiation exposure, and potentially more effective procedures.