Feature-based registration method
Methods for registering a three-dimensional model of a body volume to a real-time indication of a sensor position that involve analyzing scanned and sensed voxels and using parameters or thresholds to identify said voxels as being either tissue or intraluminal fluid. Those voxels identified as fluid are then used to construct a real-time sensed three-dimensional model of the lumen which is then compared to a similarly constructed, but previously scanned model to establish and update registration.
1. A method for registering a three-dimensional model to an image of a sensor, the method comprising:
inserting a sensor into a body lumen to acquire location data of the sensor;
assigning a density value to each voxel of a plurality of voxels of a three-dimensional model based on the acquired location data;
determining a voxel of the plurality of voxels, which is closest to the sensor, based on a plurality of parameters, each of which has a predefined threshold; and
registering the closest voxel to the acquired location data.
2. The method of claim 1 , wherein the density value is based on an advancement speed of the sensor.
3. The method of claim 1 , wherein an advancement speed of the sensor is inversely proportional to the density value.
4. The method of claim 1 , wherein the density value is a Hounsfield number.
5. The method of claim 1 , wherein the density value to each voxel is proportional to a probability that the sensor occupies each voxel.
6. The method of claim 1 , further comprising determining whether a voxel is tissue or air.
7. The method of claim 6 , wherein a voxel is determined as tissue when the density value is higher than the threshold.
8. The method of claim 6 , wherein a voxel is determined as airway when the density value is lower than the threshold.
9. The method of claim 1 , wherein registering the closest voxel includes determining whether the density value of the voxel falls within a predetermined range.
10. The method of claim 1 , wherein registering the closest voxel includes determining whether the voxel falls within a predefined proximity from a recently registered voxel.
11. The method of claim 1 , wherein registering the closest voxel includes determining whether the density value fits with a template.
12. The method of claim 11 , wherein the template is a group of continuous densities corresponding to air next to a plurality of densities corresponding to a blood vessel.
13. The method of claim 1 , wherein registering the closest voxel includes:
making a guess based on a known landmark;
temporally registering a voxel to the acquired location data based on the guess; and
determining the closest voxel that matches the plurality of parameters.
14. The method of claim 13 , further comprising calculating a difference between the temporally registered voxel and the acquired location data.
15. The method of claim 14 , wherein the closest voxel is determined based on the guess and the difference.
16. A method for registering a three-dimensional model to a sensing volume of a sensor, the method comprising:
segmenting a plurality of voxels of the three-dimensional model;
inserting a sensor into a body lumen to acquire sensing volume voxels from the sensor;
assigning a density value for each voxel of the sensing volume voxels; and
segmenting the sensing volume voxels based on a threshold; and
registering a first portion of the plurality of voxels of the three-dimensional model to the segmented sensing volume voxels.
17. The method of claim 16 , wherein the density value is based on an advancement speed of the sensor.
18. The method of claim 16 , wherein an advancement speed of the sensor is inversely proportional to the density value.
19. The method of claim 16 , wherein the density value is a Hounsfield number.
20. The method of claim 16 , wherein the density value of each voxel is proportional to a probability that the sensor occupies the voxel.
21. The method of claim 16 , wherein a voxel is considered as tissue when the density value of the voxel is higher than the threshold.
22. The method of claim 16 , wherein a voxel is considered as airway when the density value of the voxel is lower than the threshold.
23. The method of claim 16 , wherein registering the first portion includes:
calculating a difference between a value of each segmented voxel of the first portion and a value of a corresponding segmented voxel of the sensing volume voxels; and
summing differences between the first portion and the sensing volume voxels to obtain a total value.
24. The method of claim 23 , wherein registering the first portion further includes:
determining the first portion, which gives a minimum total value; and
registering the first portion, which gives the minimum total value, to the sensing volume voxels.