Dense non-rigid volumetric mapping of image coordinates using sparse surface-based correspondences
Examples of the presently disclosed technology provide systems and methods for improved image registration for image-guided brain interventions. The disclosed systems and methods use sparse surface-based correspondences between vertices of patient-specific 3D mesh representations to fit a non-rigid transformation function for estimating a deformation field that maps one cranial image (e.g., a source image used for surgical trajectory planning) to another cranial image (e.g., a reference image obtained during an image-guided brain intervention).
1 . A method, comprising:
adapting a shape-constrained deformable cranial region model to a first cranial image to generate a first patient-specific 3D mesh representation;
adapting the shape-constrained deformable cranial region model to a second cranial image to generate a second patient-specific 3D mesh representation;
using correspondences between the first and second patient-specific 3D mesh representations to fit a non-rigid transformation function;
estimating a deformation field using the non-rigid transformation function;
detecting non-rigid brain shift in a patient responsive to determining at least one of the following:
length of at least one displacement vector of the estimated deformation field exceeds a threshold length value, or
over a threshold number of displacement vectors of the estimated deformation field have lengths exceeding the threshold length value;
mapping coordinates of planned target points and entry points in the first cranial image to corresponding locations in the second cranial image using the estimated deformation field; and
displaying, on a graphical user interface (GUI), a visual representation of the second cranial image overlaid with:
visual highlights for the mapped planned target points and entry points at their corresponding locations in the second cranial image, and
a visual warning indicating the detected non-rigid brain shift.
2 . The method of claim 1 , wherein the correspondences between the first and second patient-specific 3D mesh representations comprise surface-based correspondences between mesh vertices of the first and second patient-specific 3D mesh representations.
3 . The method of claim 1 , wherein the first cranial image is a pre-operative image of a patient's cranial region used for surgical trajectory planning and the second cranial image is an intra-operative image of the patient's cranial region obtained during a surgical intervention into the patient's cranial region.
4 . The method of claim 1 , wherein the first cranial image is a brain atlas used for surgical trajectory planning and the second cranial image is an intra-operative image of a patient's cranial region obtained during a surgical intervention into the patient's cranial region.
5 . The method of claim 1 , wherein the shape-constrained deformable cranial region model comprises a computerized 3D mesh representation of a non-patient-specific human cranial region that preserves point-based correspondences during mesh adaption to patient images.
6 . The method of claim 1 , wherein the first and second cranial images comprise at least one of the following types of images:
a magnetic resonance (MR) image;
a computerized tomography (CT) image; and
a positron emission tomography (PET) image.
7 . The method of claim 6 , wherein the first and second cranial images comprise different types of images.
8 . The method of claim 1 , wherein the estimated deformation field is a dense deformation field comprising an individual displacement vector associated with each voxel of the first cranial image, the displacement vectors mapping voxels of the first cranial image to corresponding voxels of the second cranial image.
9 . Non-transitory computer-readable storage medium including instructions that, when executed by one or more processors of a computing system, cause the computing system to:
adapt a shape-constrained deformable cranial region model to a first cranial image to generate a first patient-specific 3D mesh representation;
adapt the shape-constrained deformable cranial region model to a second cranial image to generate a second patient-specific 3D mesh representation;
use surface-based correspondences between mesh vertices of the first and second patient-specific 3D mesh representations to fit a non-rigid transformation function;
estimate a deformation field using the non-rigid transformation function;
detect non-rigid brain shift in a patient responsive to determining at least one of the following:
length of at least one displacement vector of the estimated deformation field exceeds a threshold length value, or
over a threshold number of displacement vectors of the estimated deformation field have lengths exceeding the threshold length value;
map planned surgical target point and entry point coordinates from the first cranial image to the second cranial image using the estimated deformation field; and
display, on a graphical user interface (GUI), a visual representation of the second cranial image overlaid with:
visual highlights for the mapped planned target points and entry points at their corresponding locations in the second cranial image, and
a visual warning indicating the detected non-rigid brain shift.
10 . The non-transitory computer-readable medium of claim 9 , wherein the first cranial image is a pre-operative image of a patient's cranial region used for surgical trajectory planning and the second cranial image is an intra-operative image of the patient's cranial region obtained during a surgical intervention into the patient's cranial region.
11 . The non-transitory computer-readable medium of claim 9 , further comprising instructions that, when executed by the one or more processors, cause the computing system to map the first cranial image to the second cranial image.
12 . The non-transitory computer-readable medium of claim 11 , wherein the estimated deformation field is a dense deformation field comprising an individual displacement vector associated with each voxel of the first cranial image including voxels associated with the planned surgical target point and entry point coordinates, the displacement vectors mapping voxels of the first cranial image to corresponding voxels of the second cranial image.
13 . The non-transitory computer-readable medium of claim 1 , wherein the shape-constrained deformable cranial region model comprises a computerized 3D mesh representation of a non-patient-specific human cranial region that preserves point-based correspondences during mesh adaption to patient images.
14 . The non-transitory computer-readable medium of claim 9 , wherein the first and second cranial images comprise at least one of the following types of images:
a MR image;
a CT image; and
a PET image.
15 . The non-transitory computer-readable medium of claim 13 , wherein the first and second cranial images comprise different types of images.
16 . A system comprising:
one or more processing resources; and
non-transitory computer-readable medium, coupled to the one or more processing resources, having stored therein instructions that when executed by the one or more processing resources cause the system to:
adapt a shape-constrained deformable cranial region model to a first cranial image to generate a first patient-specific 3D mesh representation;
adapt the shape-constrained deformable cranial region model to a second cranial image to generate a second patient-specific 3D mesh representation;
use correspondences between mesh vertices of the first and second patient-specific 3D mesh representations to fit a non-rigid transformation function;
estimate deformation field using the non-rigid transformation function;
detect non-rigid brain shift in a patient responsive to determining at least one of the following:
length of at least one displacement vector of the estimated deformation field exceeds a threshold length value, or
over a threshold number of displacement vectors of the estimated deformation field have lengths exceeding the threshold length value; and
display, on a graphic user interface (GUI), a visual warning indicating the detected non-rigid brain shift.
17 . The system of claim 16 , wherein:
the estimated deformation field is a dense deformation field comprising an individual displacement vector associated with each voxel of the first cranial image, the displacement vectors mapping voxels of the first cranial image to corresponding voxels of the second cranial image; and
estimating non-rigid brain shift in the patient comprises determining magnitudes of displacement vectors of the estimated deformation field.
18 . The system of claim 16 , wherein the shape-constrained deformable cranial region model comprises a computerized 3D mesh representation of a non-patient-specific human cranial region that preserves point-based correspondences during mesh adaption to patient images.
19 . The system of claim 16 , wherein the correspondences between the first and second patient-specific 3D mesh representations comprise surface-based correspondences between mesh vertices of the first and second patient-specific 3D mesh representations.
20 . The system of claim 16 , wherein the visual warning indicating the detected non-rigid brain shift overlays the second cranial image of the second patient-specific 3D mesh representation.