Ultrasound Based Navigation and Control for Orthopaedic Robot Surgery. Pedro Miguel Baptista Torres. Curso de Doutoramento em Engª.

Transcription

1 Ultrasound Based Navigation and Control for Orthopaedic Robot Surgery Pedro Miguel Baptista Torres Curso de Doutoramento em Engª. Mecânica Seminário PhD Universidade de Lisboa - Instituto Superior Técnico 27/02/2014 1

2 Outline HipRob Project Overview; Research Tasks; Image Acquisition; Image Processing; Image Registration; Bone Tracking Based on 2D US Images; Conclusions; Future work; 27/02/2014 2

3 HipRob Project Overview Objectives: Development of a new robotic system to aid surgeons in performing Hip Resurfacing prosthesis surgery; Robot manipulator, is comanipulated by the surgeon during the drilling process; This system provides for the use of ultrasound images (US) to tracking the bone, instead of the usual fiducial markers; 27/02/2014 3

4 Hip Resurfacing Arthroplasty Hip Resurfacing (HR) is a bone preserving alternative method to Total Hip Replacement (THR) which maintains the anatomical loading situation of the hip almost unaffected. BHR Birmingham Hip Resurfacing System Total Hip System 27/02/2014 4

5 Smith & Nephew Birmingham Hip Resurfacing System 27/02/2014 5

6 Current 27/02/2014 6

7 HipRob: Ultrasound Based Bone Tracking 27/02/2014 7

8 Research Tasks HipRob Image Processing: Image Registration: Image Acquisition (US / CT) - Image Denoising; - Segmentation; - 3D Surface Reconstruction; Pre-operative data: CT images Intra-operative data: US images Robot Control based in US visual information 27/02/2014 8

9 Image Acquisition Non Freehand US Acquisition System Freehand US Acquisition System w P = w T b b T e e T pr pr T i i P(u, v) NDI P = NDI T MK MK T pr pr T i i P(u, v) 27/02/2014 9

10 Image Acquisition 27/02/

11 Image Processing Segmentation Method: 1. Initialization (ϕ(u,v), t = 0); 2. Compute c 1 (ϕ) and c 2 (ϕ); 3. Evolve the level set function; 4. Let ϕ(u,v) = 1 if ϕ(u,v) > 0; otherwise ϕ(u,v) = -1; 5. Regularize the level set function with a Gaussian filter: ϕ u, v = ϕ u, v G σ 6. If method converge ϕ(u,v) representd the image segmentation; Else, return to the step 2; c 1 ϕ = c 2 ϕ = ϕ t spf I u, v = I u, v H ϕ dudv Ω H ϕ dudv I u, v (1 H ϕ dudv) Ω (1 H ϕ dudv) Ω Ω = spf(i(u, v)) α ϕ I u, v c 1 + c 2 2 max I(u, v) c 1 + c 2 2 c 2 i c 1 i = c 2 i 1 c 1 i 1 27/02/

12 Segmentation results of the image with index 100 : Image Processing Segmentation Results With Denoising: Original Method: Without Denoising: 27/02/

13 Image Processing Segmentation Results Method RMSE[pixel] σ RMSE DM[pixel] σ DM Proposed FMS SDS GACS TLSS MRIS Average of seconds per image. 27/02/

14 Image Processing Segmentation Results 27/02/

15 Image Processing Point Cloud Extraction US point cloud CT point clouds points points points 27/02/

16 Image Processing Reconstruction and Visualization Volume Rendering Method based on Maximum Intensity Projection (MIP) Algorithm 27/02/

17 Image Resistration - ICP Euclidian Distance: 27/02/

18 Navigation System Calibration CT T NDI = T R2 T R1 offset 27/02/

19 Bone Tracking Based on 2D US Images 27/02/

20 Robot Navigation CT P drill = CT T NDI NDI P drill ROB P drill k = NDI T ROB 1 CT T NDI 1 T R k CT P drill 27/02/

21 Experimental Setup 27/02/

22 Experimental Results - Segmentation Segmentation erros (computed in 599 images): RMSE σ RMSE DM σ DM [pixel] [mm] /02/

23 Experimental Results - Calibration Method 1 Method 2 Calibration erros: Registration Error H dist [mm] Method Method /02/

24 Experimental Results On-line Registration On-line Registration errors: Registration Results Before Registration H dist [mm] After Registration H dist [mm] Time [s] /02/

25 Experimental Results - Tracking norm Std Máx min Position [mm] Orientation [degree] norm δx δy δz Position [mm] Orientation [degree] /02/

26 Conclusions A new region-based approach to image segmentation, was proposed; The experimental results in US and CT images, show that the method presents better accuracy than other methods; A new approach to the control loop for surgical robots navigation was presented; Contrary to current surgical systems, it do not use any type of implant in the bone, to track the femur movements; A KUKA lightweight robot was used to validate the applicability of the tracking system in the experimental tests carried out on a femur phantom; In most experiments the update was always validated, with errors minors than 2 mm / 5º. 27/02/

27 Future Work Optimize the image processing and registration tasks to improve processing times and the robustness of the system; It is intended extract some features (e.g shape, curvature) of point clouds to improve registration results; Perform experimental tests on corpses ; 27/02/

28 HipRob 27/02/

29 Ultrasound Based Navigation and Control for Orthopaedic Robot Surgery Pedro Miguel Baptista Torres Curso de Doutoramento em Engª. Mecânica Thank you for your attention This work was partly supported by the Strategic Project, P Est-OE/EME/LA0022/2011, through FCT (under IDMEC-IST, Research Group: IDMEC/LAETA/CSI), FCT project PT DC/EME- CRO/099333/2008 and EU FP7 ICT , project ECHORD. 27/02/