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Deep segmentation leverages geometric pose estimation in computer-aided total knee arthroplasty.

Pedro Rodrigues¹, Michel Antunes², Carolina Raposo²

¹Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal.

Healthcare Technology Letters

|February 11, 2020

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This study introduces a novel computer-aided navigation system for total knee arthroplasty. The system uses affordable cameras for contactless implant positioning, improving surgical accuracy without extra incisions or markers.

Area of Science:

Orthopedic surgery
Medical imaging
Computer-assisted surgery

Background:

Knee arthritis often necessitates total knee arthroplasty (TKA).
Accurate implant positioning is crucial for TKA success but challenging.
Current navigation systems often rely on costly, invasive markers.

Purpose of the Study:

To present a proof-of-concept for a novel, markerless computer-aided navigation system for TKA.
To support surgeons in adhering to preoperative plans during surgery.
To reduce reliance on expensive and invasive tracking technologies.

Main Methods:

A computer-aided system utilizing consumer RGB and depth cameras.
Deep learning for bone surface segmentation.
A registration algorithm for contactless sensor pose estimation relative to a preoperative 3D model.

Keywords:

RGB cameras bone bone surface computed tomography scan computer-aided system computer-aided total knee arthroplasty deep learning approach deep segmentation depth cameras diseases geometric pose estimation image registration image segmentation joint disease knee arthritis learning (artificial intelligence)magnetic resonance imaging medical image processing navigation sensor navigation system neural nets orthopaedics pose estimation preoperative 3D model prosthetics surgery surgical flow

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Main Results:

Demonstrated contactless pose estimation of the navigation sensor.
Validated the system's effectiveness using ex-vivo data.
Provided valuable intraoperative guidance information for surgeons.

Conclusions:

The proposed system offers a cost-effective, non-invasive alternative for surgical navigation in TKA.
This technology has the potential to enhance the precision and efficiency of total knee replacement procedures.