Method and apparatus for three dimensional reconstruction of a joint using ultrasound
A method of generating a 3-D patient-specific bone model, the method comprising: (a) acquiring a plurality of raw radiofrequency (“RF”) signals from an A-mode ultrasound scan of a patient's bone at a plurality of locations using an ultrasound probe that comprises a transducer array; (b) tracking the acquiring of the plurality of raw RF signals in 3-D space and generating corresponding tracking data; (c) transforming each of the plurality of raw RF signals into an envelope comprising a plurality of peaks by applying an envelope detection algorithm to each of the plurality of raw RF signals, each peak corresponding with a tissue interface echo; (d) identifying a bone echo from the tissue interface echoes of each of the plurality of raw RF signals to comprise a plurality of bone echoes by selecting the last peak having a normalized envelope amplitude above a preset threshold, wherein the envelope amplitude is normalized with respect to a maximum peak existing in the envelope; (e) determining a 2-D bone contour from the plurality of bone echoes corresponding to each location of the ultrasound probe to comprise 2-D bone contours; (f) transforming the 2-D bone contours into an integrated 3-D point cloud using the tracking data; and, (g) deforming a non-patient specific 3-D bone model corresponding to the patient's bone in correspondence with the integrated 3-D point cloud to generate a 3-D patient-specific bone model.
1. A method of generating a 3-D patient-specific bone model, the method comprising: acquiring a plurality of raw signals from an A-mode ultrasound scan of a patient's bone at a plurality of locations using an ultrasound probe that comprises a transducer array; tracking the acquiring of the plurality of raw signals in 3-D space using a position tracking device and generating corresponding tracking data; applying model-based signal processing to each of the plurality of raw signals resulting in processed signals: transforming the processed signals into an envelope comprising a plurality of peaks by applying an envelope detection algorithm to the processed signals, each peak corresponding with a tissue interface echo; identifying a bone echo from the tissue interface echoes of each of the processed signals to comprise a plurality of bone echoes by selecting the last peak having a normalized envelope amplitude above a preset threshold, wherein the envelope amplitude is normalized with respect to a maximum peak existing in the envelope; determining a 2-D bone contour from the plurality of bone echoes corresponding to each location of the ultrasound probe to comprise 2-D bone contours; transforming the 2-D bone contours into an integrated 3-D point cloud using the tracking data; and deforming a non-patient specific 3-D bone model corresponding to the patient's bone in correspondence with the integrated 3-D point cloud to generate a 3-D patient-specific bone model.
2. The method of claim 1 , wherein applying an envelope detection algorithm to each of the plurality of raw signals comprises applying a moving power filter to each of the plurality of raw signals.
3. The method of claim 1 , wherein the position tracking device includes an optical position tracking system, an electromagnetic position tracking system, or a radiofrequency position tracking system.
4. The method of claim 1 , wherein the non-patient specific 3-D bone model is utilized to filter noise by thresholding for a distance between a respective point of the integrated 3-D point cloud and the non-patient specific 3-D bone model.
5. The method of claim 1 , further comprising identifying the 2-D bone contour by removing portions of the bone echo in each sample that deviate from a continuous portion of the bone echo.
6. The method of claim 1 , wherein the non-patient specific 3-D bone model is an average bone model of a plurality of bone models in a statistical atlas.
7. The method of claim 1 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.
8. The method of claim 1 , wherein deforming the non-patient specific 3-D bone model comprises:
comparing the non-patient specific 3-D bone model with the point cloud; and
based on the comparing, deforming the non-patient specific 3-D bone model to match the point cloud.
9. The method of claim 8 , wherein the comparing and deforming are iteratively performed until the comparing results in a deviation that is less than a deviation threshold.
10. The method of claim 1 , wherein the 3-D patient-specific bone model includes a 3-D patient-specific model of a bone, a 3-D patient-specific model of a joint, a 3-D patient-specific model of cartilage, or combination thereof.
11. The method of claim 2 , wherein tracking the acquisition includes an optical position tracking system, an electromagnetic position tracking system, or a radiofrequency position tracking system.
12. The method of claim 2 , wherein the non-patient specific 3-D bone model is utilized to filter noise by thresholding for a distance between a respective point of the integrated 3-D point cloud and the non-patient specific 3-D bone model.
13. The method of claim 3 , wherein the non-patient specific 3-D bone model is utilized to filter noise by thresholding for a distance between a respective point of the integrated 3-D point cloud and the non-patient specific 3-D bone model.
14. The method of claim 2 , further comprising identifying the 2-D bone contour by removing portions of the bone echo in each sample that deviate from a continuous portion of the bone echo.
15. The method of claim 3 , further comprising identifying the 2-D bone contour by removing portions of the bone echo in each sample that deviate from a continuous portion of the bone echo.
16. The method of claim 4 , further comprising identifying the 2-D bone contour by removing portions of the bone echo in each sample that deviate from a continuous portion of the bone echo.
17. The method of claim 2 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.
18. The method of claim 3 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.
19. The method of claim 4 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.
20. The method of claim 5 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.
21. The method of claim 6 , wherein transforming the 2-D bone contours into an integrated 3-D point cloud further comprises:
transforming the 2-D bone contours from a local frame of reference into 3-D bone contours in a world frame of reference; and
integrating the transformed 3-D bone contours to form the integrated 3-D point cloud.