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Objectives

Founded by surgeons, scientists, and engineers from Queen Mary Hospital, HKU, Cambridge and Silicon Valley, Digital Health Laboratory | AIMed commits to investigate the cutting-edge AI techniques for clinical applications, including:

  • Enable AI integrated modelling with applications in fields including optimised surgical planning, 3D printing of personalized implants and robotic surgery navigation.

  • Launch standardized and secured clinical big data center for disease progression prediction, automated patient follow-ups and subjects recruitment for clinical research.

Numerical modeling

Holographic sensing and Visualization

Holographic sensing and display system to simulate accurate or mobile geometries of body parts and/or implants, as well as visualize the geometry of the implants and/or the complex pathological parts for the purpose like teaching, pre-operative planning, surgical training, preparation for 3D printing and prototyping, development of the complex matrix for bio-printing, etc.​

Resources for Deep Learning

Enhancement of computational hardware for deep learning for grant-funded and self-initiated projects, and providing servers to multiple departments for clinical big data analysis, integrated with the most advanced hardware and software architecture, i.e. GPU speed up, training distribution.

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  • MRP/038/20X - A Non-radiation Artificial Intelligence Spine Deformity Diagnosis Dystem

  • ITS/404/18 - A Novel Mobile Application Enabling Automated Body Contour Comparison and Spine Alignment Examination Using Artificial Intelligence

  • ITS/470/16 - A Novel Osteoporotic Bone Fracture Simulation System Enabling Safer and More Effective Fracture Fixation Surgery and Implant Design for Elderly Patients

  • Hospital Authority HADCL Project A000005 - Automatic hip fractures detection using deep learning

  • AI (computer vision) segmentation of spine, knee, hip and shoulder and recognition of fracture pathologies for 3D printing and surgical guidance

  • AI (natural language) analysis of disease natural history and clinical notes in treatment response predictions and automated treatment planning

Highly secured and encrypted technology and the environment with localized cloud engine

  • Increased the using efficiency of the hardware (GPUs)

  • Ensure the security of clinically relevant information

Applied modeling

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Medical 3D printing​

  • High-temperature Laser sintering PEEK 3D Printer for the fabrication of custom-made implants and very high-grade industrial prototypes.

  • Polyjet printer for multicolored soft anatomical models for surgical simulation, teaching, and planning.

  • 260 cases have been completed by the existing clinician-researcher led Anatomy Modelling Laboratory using only one lower technology FDM 3D printer despite significant limitations.

World-class pre-clinical prototyping​

  • Multi-axis sinker EDM services and multi-axis machining allowing the operators to produce complex shapes with high accuracy.

  • Multi-axis turning of prototyped implants with the digital controlled lathe.

  • Advanced finishing technologies for antiseptic purpose and/or healing acceleration.

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Implant quality control and performance testing

  • Advanced medical robotics include motion and stress simulation robot, exoskeleton and the surgical robot can upgrade the existing biomechanical simulation platform to a multipurpose robotic system. Thus, high-fidelity biomechanical conditions can be simulated in the laboratory environment, and automated navigated robotic surgeries can be investigated.

  • Students and engineers can be trained with cutting edge testing equipment supervised by experts from clinical, scientific, and industrial fields.

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