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Image Guided Navigation System for Minimally Invasive Surgery. Hua Zhong October 2007. Outline. Minimally Invasive Surgery Registration and Navigation System Overview Ultrasound Virtual Touch 4D Registration Non-rigid Registration Visualization. Minimally Invasive Surgery. - PowerPoint PPT Presentation
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IMAGE GUIDED NAVIGATION SYSTEM FOR MINIMALLY INVASIVE SURGERYHua ZhongOctober 2007
Outline
Minimally Invasive Surgery Registration and Navigation System
Overview Ultrasound Virtual Touch 4D Registration Non-rigid Registration Visualization
What is minimally invasive surgeryBenefits & limitations
Minimally Invasive Surgery
Minimally Invasive Surgery
Catheter
Minimally Invasive Surgery
Minimally Invasive Surgery
What are currently available systemsHow do they workLimitations
Registration & Navigation Systems
Registration & Navigation Systems
CT image segmented 3D model reconstructed from CT
Registration & Navigation Systems
Magnetic Transmitter
Bed
Catheter
Catheter Tip
Example system: Biosense Carto Merge System
Registration & Navigation Systems Limitations 1: radiation Limitations 2: manually collect surface
points Limitations 3: low accuracy
Touch with ultrasoundUltrasound image plane thickness correctionRegistration with virtual touch points
Ultrasound Virtual Touch
Ultrasound Virtual Touch
Ultrasound Virtual Touch
Ultrasound Virtual Touch
Position Sensor Video
Ultrasound Virtual Touch
Virtual Touch Video
Ultrasound Virtual Touch
Virtual TouchVirtual Touch12000+ points ~3 minutes12000+ points ~3 minutes
Manual physical touchManual physical touch 88 points ~20 minutes88 points ~20 minutes
Ultrasound Virtual Touch
31 63 127 1278 127810
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Point Set Size
Re
gis
tra
tio
n S
uc
ce
ss
ful R
ate
Registration Successful Rate VS. Point Set Size
6%
20%
50%
96%99%
31 63 127 1278 127810
1
2
3
4
5
6
7
8
9
10
11
12
Point Set Size
Av
era
ge
Re
gis
tra
tio
n E
rro
r (m
m)
Average Registration Error VS. Point Set Size
11.58mm
8.78mm
4.91mm
0.95mm
0.09mm
Ultrasound Virtual Touch
Ultrasound Image Thickness
Ultrasound Image Thickness
Ultrasound Image Thickness
Thickness of ultrasound image plane, also called beam width: 5-8mm
Size of left atrium: 70-100mm First we need to measure the thickness
Measure Image ThicknessRichard, B.: Test object for measurement of section thickness at us. Radiology 211 (1999) 279-282Skolnick, M.: Estimation of ultrasound beam width in the elevation (section thick-ness) plane. Radiology 180 (1991) 286-288
45˚
Band Width
Transducer
Measure Image Thickness
Precise built of model Precise motion of the plane or multiple
planes Can we reduce all those restrictions?
Measure Image Thickness
Transducer
Measure Image Thickness
β
Measure Image Thickness
Measure β in ultrasound images
Measure Image Thickness
W is the width of the white band in ultrasound imageα is the angle of the sloped plane which can be measured
α= 45˚ , β= 0˚ : Thickness = w
Measure Image Thickness
Move the slope around Measure thickness at various depth Interpolate sample thickness to generate
a continuous function: Thickness = f(depth)
Measure Image Thickness
Correct Error from Image Thickness
1. Position and orientation of the ultrasound image plane.
2. Thickness of the image at point o.
3. Local normal of the object surface.
If we know these 3 things, we can correct the error!
Correct Error from Image Thickness
Correct Error from Image Thickness
Correct Error from Image Thickness
Correct Error from Image Thickness
Correct Error from Image Thickness1. Position and orientation of the
ultrasound image plane. 2. Thickness of the image at point o. 3. Local normal of the object surface.
YesYesYesYes
??
Correct Error from Image ThicknessEstimate local surface normalEstimate local surface normal By fitting local registration points
By pre-registration
Correct Error from Image ThicknessEstimate local surface normalEstimate local surface normal
Estimated surface normal will only be used to determine which of P1 or P2 is the real surface point.
It doesn’t need to be very accurate.
Correct Error from Image Thickness1. Position and orientation of the
ultrasound image plane. 2. Thickness of the image at point o. 3. Local normal of the object surface.
YesYesYesYes
YesYes
Correct Error from Image Thickness Experiment Design:1. Different group with various average
intersecting angles
Correct Error from Image Thickness The error is dependent on intersecting
angle: smaller the angle larger the error
Prager, R.W., Rohling, R.N., Gee, A.H., Berman, L.: Rapid calibration for 3-dfreehand ultrasound. In: Ultrasound in Medicine and Biology. (1998) 24(6):855-869
a
bo
o’ a
b
o
o’
Correct Error from Image Thickness Experiment Design:1. Different group with various average
intersecting angles2. Register to the surface model without
correction3. Register to the surface model with
correction4. Separate evaluation point set
Correct Error from Image Thickness Expected result
Intersecting angle
Regis
trati
on E
rror
Un-correct points
Corrected points
Correct Error from Image Thickness
Correct Error from Image Thickness Registration error around 1.8-1.9mm Average accuracy boost: 20.45% Consistent accuracy across the spectrum
Conclusion for “Virtual Touch” Faster More accurate More consistent
Time-space registration for heart model with full motion.
4D Registration
4D Registration
4D Heart Model Movie
4D Registration
Capture multiple 3D models during a cardiac cycle
4D Registration
Heart shape changes from cardiac cycle Heart shape also change from breath
cycle
Lung
Left atrium
4D Registration
Shape changes from breath
Location measured at heart wallShif
t d
uri
ng d
iffere
nt
bre
ath
phase
(m
m)
4D Registration
Two cycles are independent to each other Have to remove one cycle and
synchronize all shape change to the other cycle
Remove breath cycle with high-frequency ventilation machine: it pumps in and out a little air at a high frequency, and the pressure in lung can be seen as constant.
4D Registration
4D Registration
Given SpaceRegistration
SurfacePoints
HeartModel
Given Time RegistrationR,T
S
4D Registration
EM Hidden variable: time-alignment Iterate: 1. fix time alignment find space
registration2. fix space registration find time
alignmentvideo
Some small non-homogeneous local shape changes cannot be found by global rigid registration. We add a non-rigid local registration component.
Non-rigid Registration
Non-rigid Registration
Location measured at heart wallShif
t d
uri
ng d
iffere
nt
bre
ath
phase
(m
m)
Non-rigid Registration
Non-rigid Registration
For any surface points For any surface points ppii its nearest point on the model is its nearest point on the model is CCpipi
After registration, our system can visualize the heart model and catheters in various ways to make navigation easy and intuitive.
Visualization
Visualization
Visualization
Visualization
Visualization
video
Acknowledgement
Takeo Kanade, David Schwartzman, Yanxi Liu, George StettenBranislav Jaramaz, Jianbo Shi, Louise Ditmore, Sharon & Deborah
Questions
Thank you!