Claims Analysis
Total Claims: 18
Claim 1
Independent Claim
176 words
A method for generating a three-dimensional representation of a region of tissue scanned by a transducer, comprising the following steps: A) pre-determining a calibrated speckle correlation-versus-distance function for the transducer to be used, for the tissue to be scanned, or both; B) generating a series of 2-D image frames, divided into image elements; C) identifying image elements representing speckle; D) for each scanned image frame, estimating actual speckle correlation with at least one other frame based on at least the image elements in corresponding portions of the respective frames; E) estimating the distance between pairs of image frames by evaluating the correlation-versus-distance function with the corresponding estimated actual speckle correlation for the pairs of frames, including estimating the distance between a reference and at least one other image frame; F) for each frame for which correlation has been estimated, determining its relative displacement from the reference by evaluating the correlation-versus-distance function with the estimated actual speckle correlation; G) registering the different frames in a three-dimensional format as a 3-D representation; and H) displaying the 3-D representation.
Claim 2
Independent Claim
176 words
A method for generating a three-dimensional representation of a region of tissue scanned by a transducer, comprising the following steps: A) pre-determining a calibrated speckle correlation-versus-distance function for the transducer to be used, for the tissue to be scanned, or both; B) generating a series of 2-D image frames, divided into image elements; C) identifying image elements representing speckle; D) for each scanned image frame, estimating actual speckle correlation with at least one other frame based on at least the image elements in corresponding portions of the respective frames; E) estimating the distance between pairs of image frames by evaluating the correlation-versus-distance function with the corresponding estimated actual speckle correlation for the pairs of frames, including estimating the distance between a reference and at least one other image frame; F) for each frame for which correlation has been estimated, determining its relative displacement from the reference by evaluating the correlation-versus-distance function with the estimated actual speckle correlation; G) registering the different frames in a three-dimensional format as a 3-D representation; and H) displaying the 3-D representation.
Claim 3
Dependent Claim
98 words
A method as defined in claim 1, further including the following steps: dividing each scanned image frame into a pattern of the sub-frames, each sub-frame comprising a pre-determined sub-set of the image elements in the scanned image frame and corresponding to one sub-frame in at least one other scanned image frame; identifying certain ones of the sub-frames in each scanned image frame as speckle sub-frames; and estimating the actual speckle correlation between pairs of scanned image frames as a predetermined function of actual speckle correlation between corresponding pairs of speckle sub-frames in the pairs of scanned image frames.
Claim 4
Dependent Claim
65 words
A method as defined in claim 2, further including following steps: for each corresponding pair of sub-frames in predetermined pairs of scanned image frames, computing a sub-frame correlation value; and determining a sub-frame distance between the predetermined pairs of scanned image frames as a predetermined function of the sub-frame correlation values of the image frames whose correlation values exceed a predetermined minimum correlation reliability value.
Claim 5
Dependent Claim
64 words
A method as defined in claim 2, further including the following steps: generating a plurality of the 2-D image frames to be non-parallel, the displacement of each such non-parallel frame from the reference thereby having a rotational component; and estimating angular displacement of adjacent non-parallel image frames as a predetermined function of the distance estimates of corresponding sub-frames of the adjacent non-parallel image frames.
Claim 6
Dependent Claim
73 words
A method as defined in claim 2, further including the following steps: estimating a local transducer velocity over a plurality of image frames; calculating a frame velocity for each of selected ones of the scanned image frames; comparing each frame velocity with the estimated local transducer velocity; and marking as a spurious frame any frame whose frame velocity differs by more than a predetermined velocity threshold function value from the local transducer velocity.
Claim 7
Dependent Claim
64 words
A method as defined in claim 5, further including the following steps: calculating a velocity-based distance value for each spurious frame, wherein the velocity-based distance value is defined as the product of the local transducer velocity and a predetermined time value; and for each spurious frame, setting its distance from the reference equal to a predetermined functional value of the corresponding velocity-based distance value.
Claim 8
Dependent Claim
118 words
A method as defined in claim 2, further including the following steps: for each corresponding pair of sub-frames in predetermined pairs of scanned image frames, computing a sub-frame correlation value; determining a sub-frame distance between the pairs of sub-frames by evaluating the correlation-versus-distance function with the sub-frame correlation values; for each corresponding pair of speckle sub-frames in the pairs of scanned image frames, estimating a sub-frame transducer velocity value; calculating a frame velocity; comparing each sub-frame velocity with the frame velocity; and estimating the relative displacement of the frames as a predetermined function of the sub-frame distances for only those sub-frames whose sub-frame transducer velocity values differ by less than predetermined functional reliability value from the frame velocity.
Claim 9
Dependent Claim
121 words
A method as defined in claim 1, further including the following steps: dividing each scanned image frame into a pattern of the sub-frames, each sub-frame comprising a pre-determined sub-set of the image elements in the scanned image frame and corresponding to one sub-frame in at least one other scanned image frame; for each sub-frame of each scanned image frame, estimating a sub-frame speckle probability, defined as the probability that the sub-frame represents a speckle region of the tissue; for each corresponding pair of sub-frames in predetermined pairs of scanned image frames, computing a sub-frame correlation value; and determining a distance between the predetermined pairs of scanned image frames as a predetermined function of the sub-frame correlation values of the image frames.
Claim 10
Dependent Claim
59 words
A method as defined in claim 8, further including the step of computing a weight for each sub-frame correlation value as a predetermined function of the speckle probability for the corresponding sub-frame; in which: the step of determining the distance comprises forming a weighted average of the sub-frame correlation values and evaluating the correlation-versus-distance function using the weighted average.
Claim 11
Dependent Claim
87 words
A method as defined in claim 2, further including the following steps: for each corresponding pair of sub-frames in predetermined pairs of scanned image frames, computing a sub-frame correlation value; computing a weight for each sub-frame correlation value as a predetermined function of the distance of each speckle sub-frame from a focal region of the transducer; and determining the distance between the predetermined pairs of scanned image frames by forming a weighted average of the sub-frame correlation values and evaluating the correlation-versus-distance function using the weighted average.
Claim 12
Dependent Claim
99 words
A method as defined in claim 1, further including the following steps: for selected pairs of image frames for which at least one intermediate image frame is located between them, designating the frames in the selected pairs as end frames; selecting a plurality of combinations of the end frames and of the intermediate frames; summing the estimated distances between all adjacent pairs of the end frames and the intermediate frames to form a possible total distance; and estimating the distance between the end frames as a predetermined function of the possible total distances for the selected plurality of combinations.
Claim 13
Dependent Claim
73 words
A method as defined in claim 1, further including the following steps: estimating a local transducer velocity over a plurality of image frames; calculating a frame velocity for each of selected ones of the scanned image frames; comparing each frame velocity with the estimated local transducer velocity; and marking as a spurious frame any frame whose frame velocity differs by more than a predetermined velocity threshold function value from the local transducer velocity.
Claim 14
Dependent Claim
64 words
A method as defined in claim 12, further including the following steps: calculating a velocity-based distance value for each spurious frame, wherein the velocity-based distance value is defined as the product of the local transducer velocity and a predetermined time value; and for each spurious frame, setting its distance from the reference equal to a predetermined functional value of the corresponding velocity-based distance value.
Claim 15
Dependent Claim
48 words
A method as defined in claim 1, further including the following steps: generating the 2-D image frames as planes extending in a depth direction; and compensating the image frames for transducer motion in the depth direction before the step of registering the different frames in a three-dimensional format.
Claim 16
Dependent Claim
44 words
A method as defined in claim 1, further including the following steps: carrying out steps A)-F) for a plurality of scans of the region, each scan extending in a different principal direction; and registering the frames of all scans into a single 3-D registration.
Claim 17
Independent Claim
206 words
A system for generating a three-dimensional representation of a region of tissue including: A) an ultrasonic transducer scanning the region as a series of 2-D image frames, each frame comprising a pattern of image elements; B) processing means: 1) for identifying in each 2-D image frame image elements representing speckle; 2) for each scanned image frame, for estimating actual speckle correlation with at least one other frame based on at least the image elements in corresponding portions of the respective frames; 3) for estimating the distance between pairs of image frames by evaluating a predetermined calibrated correlation-versus-distance function with the corresponding estimated actual speckle correlation for the pairs of frames, including estimating the distance between a reference and at least one other image frame; 4) for each frame for which correlation has been estimated, for determining its relative displacement from the reference by evaluating the correlation-versus-distance function with the estimated actual speckle correlation; and 5) for registering the different frames in a three-dimensional format as a 3-D representation; C) a memory including a 2-D frame data portion for storing the 2-D image frames and a correlation data portion for storing predetermined parameters of the correlation-versus-distance function; and D) a display means for displaying the 3-D representation.
Claim 18
Independent Claim
206 words
A system for generating a three-dimensional representation of a region of tissue including: A) an ultrasonic transducer scanning the region as a series of 2-D image frames, each frame comprising a pattern of image elements; B) processing means: 1) for identifying in each 2-D image frame image elements representing speckle; 2) for each scanned image frame, for estimating actual speckle correlation with at least one other frame based on at least the image elements in corresponding portions of the respective frames; 3) for estimating the distance between pairs of image frames by evaluating a predetermined calibrated correlation-versus-distance function with the corresponding estimated actual speckle correlation for the pairs of frames, including estimating the distance between a reference and at least one other image frame; 4) for each frame for which correlation has been estimated, for determining its relative displacement from the reference by evaluating the correlation-versus-distance function with the estimated actual speckle correlation; and 5) for registering the different frames in a three-dimensional format as a 3-D representation; C) a memory including a 2-D frame data portion for storing the 2-D image frames and a correlation data portion for storing predetermined parameters of the correlation-versus-distance function; and D) a display means for displaying the 3-D representation.