Systems and methods to detect and display endovascular features
In part, the disclosure relates to method for identifying regions of interest in a blood vessel. The method includes the steps of: providing OCT image data of the blood vessel; applying a plurality of different edge detection filters to the OCT image data to generate a filter response for each edge detection filter; identifying in each edge detection filter response any response maxima; combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered OCT data; and analyzing the edge filtered OCT data to identify a region of interest, the region of interest defined as a local cluster of response maxima. In one embodiment, one or more indicia are positioned in one or more panels to emphasize a reference vessel profile as part of a user interface.
1. A method for identifying regions of interest in a blood vessel, the method comprising the steps of:
providing intravascular image data of the blood vessel;
applying a plurality of different edge detection filters to the intravascular image data to generate a filter response for each edge detection filter;
identifying in each edge detection filter response any response maxima, a local response maxima representing detected edges;
combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered intravascular data;
analyzing the edge filtered intravascular data to identify a region of interest, the region of interest defined as a local cluster of response maxima; and
identifying the region of interest as a calcified region if the region of interest includes at least one vertical edge response maxima,
wherein the plurality of different edge detection filters includes a horizontal edge detection filter and a vertical edge detection filter
wherein the vertical edge detection filter comprises a left edge detection filter and a right edge detection filter.
2. The method of claim 1 , wherein the edge detection filters are based on Gaussian derivatives.
3. The method of claim 1 , wherein the intravascular image data is formatted in polar space or comprises a polar image.
4. The method of claim 1 , wherein the intravascular image data is formatted in Cartesian space or comprises a cross-sectional image.
5. The method of claim 1 , wherein the horizontal edge detection filter comprises a top edge filter and a bottom edge filter.
6. The method of claim 1 , wherein the local maxima are determined by comparing filter responses to a predetermined threshold.
7. The method of claim 1 , wherein the plurality of filters comprises at least a top edge filter, a left edge filter, and a right edge filter.
8. A method for identifying regions of interest in a blood vessel, the method comprising the steps of:
providing intravascular image data of the blood vessel;
applying a plurality of different edge detection filters to the intravascular image data to generate a filter response for each edge detection filter;
identifying in each edge detection filter response any response maxima, a local response maxima representing detected edges;
combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered intravascular data;
analyzing the edge filtered intravascular data to identify a region of interest, the region of interest defined as a local cluster of response maxima; and
identifying the region of interest as a non-calcified region if the region of interest includes no vertical edge response maxima,
wherein the plurality of different edge detection filters includes a horizontal edge detection filter and a vertical edge detection filter,
wherein the vertical edge detection filter comprises a left edge detection filter and a right edge detection filter.
9. A method for identifying regions of interest in a blood vessel, the method comprising the steps of:
providing intravascular mage data of the blood vessel;
applying a plurality of different edge detection filters to the intravascular image data to generate a filter response for each edge detection filter;
identifying in each edge detection filter response any response maxima, a local response maxima representing detected edges;
combining the response maxima for each edge detection filter response while maintaining the spatial relationship of the response maxima, to thereby create edge filtered intravascular data;
analyzing the edge filtered intravascular data to identify a region of interest, the region of interest defined as a local cluster of response maxima;
repeating preceding steps for a plurality of intravascular image frames; and
rendering a two- or three-dimensional model of the blood vessel using the plurality of intravascular image frames, based on the intravascular edge filtered data and the regions of interest,
wherein the model is a three-dimensional longitudinal rendering of the blood vessel, the model including a graphic for indicating a length of the region of interest, the graphic comprising a ring coaxial with the blood vessel with the blood vessel extending through the ring, the ring having a first indicia proportional to the length of healthy tissue and a second indicia proportional to the length of the region of interest.