CN109493943B - Three-dimensional visual scalp craniotomy positioning method combined with optical surgical navigation - Google Patents
Three-dimensional visual scalp craniotomy positioning method combined with optical surgical navigation Download PDFInfo
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30016—Brain
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- G—PHYSICS
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30096—Tumor; Lesion
Abstract
The invention discloses a three-dimensional visual craniotomy positioning method combined with optical surgical navigation, which comprises the following steps: 1) introducing a patient craniocerebral CT image sequence for segmentation to obtain two-dimensional image data of intracranial lesions and scalp; 2) performing three-dimensional reconstruction according to two-dimensional images of the focus and the scalp, rendering the two-dimensional images into a three-dimensional model in a virtual space, and orthogonally mapping the focus model to a scalp design self-adaptive craniotomy contour; 3) after the registration of the surgical tool and the registration of the patient space and the virtual space are completed by combining an optical surgical navigator, tracking the surgical tool in real time, and drawing an actual craniotomy contour on the real craniocerebral scalp along the virtual craniotomy contour; 4) recording and displaying the moving path of the needle point of the surgical tool in real time by adopting a visualization method; 5) and under the virtual space, solving the distance between the actual contour and the design contour to evaluate the precision of craniotomy positioning. The invention provides a sketching reference for doctors, and overcomes the defect that the craniotomy contour needs to be designed by staring at a focus with naked eyes in the traditional method.
Description
Technical Field
The invention relates to the technical field of medical image processing and surgical application, in particular to a three-dimensional visual scalp craniotomy positioning method combined with optical surgical navigation.
Background
Craniocerebral surgery has the characteristics of high risk, high difficulty and the like, positioning of a craniotomy incision according to the position of a focus is an important step of craniotomy, and the positioning precision can directly influence the operation quality and postoperative rehabilitation of a patient. Neurosurgeons typically design craniotomy incisions and then remove lesions with clinical experience using tumor information displayed by medical images such as CT, MRI, and the like. The position of a tumor is difficult to accurately position only by two-dimensional image data during preoperative planning, so that the incision design is often larger or the positioning is inaccurate, the incision may need to be repositioned during the operation, and a larger wound is caused to a patient.
Currently, an optical surgical navigation system can display a three-dimensional model of a lesion and a scalp and accurately position an intracranial lesion, and a doctor needs to look at a screen closely and design a craniotomy incision on the head of a patient along the contour of the lesion by using a surgical tool. However, observation of the lesion contour from a single three-dimensional view angle results in a large included angle between the surgical tool and the scalp, which is prone to cause inaccuracy in incision design due to improper operation; meanwhile, the mainstream surgical navigation system does not feed back the contour delineation process, so that the delineation result cannot be corrected. In addition, no standardized outline delineation evaluation method exists at present, and the design result of the notch cannot be quantized.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a three-dimensional visual scalp craniotomy positioning method combined with optical operation navigation, realizes craniotomy contour positioning and design combined with an optical operation navigation system, and provides a set of standardized contour delineation evaluation method for quantifying delineation accuracy.
In order to achieve the purpose, the technical scheme provided by the invention is as follows: a three-dimensional visual scalp craniotomy positioning method combined with optical operation navigation is characterized in that a three-dimensional model of a focus and a scalp is taken as a basis, the outline of the focus model is orthogonally projected onto the scalp model according to the minimum principle of operation injury to generate a self-adaptive craniotomy outline, then the virtual craniotomy outline is sketched onto the surface of a real craniotomy brain by combining with the optical operation navigation, and the precision of the craniotomy outline positioning is further evaluated by means of indexes, and the method comprises the following steps:
1) performing three-dimensional reconstruction according to CT images of the focus and the scalp, rendering the images into a three-dimensional model in a virtual space, and orthogonally mapping the focus model to a self-adaptive craniotomy contour designed on the scalp after selecting an angle of view with small surgical injury through rotating the model;
2) after the registration of the surgical tool and the registration of the patient space and the virtual space are completed by combining an optical surgical navigator, tracking the surgical tool in real time, and drawing an actual craniotomy contour on the real craniocerebral scalp along the virtual craniotomy contour;
3) recording and displaying the moving path of the needle point of the surgical tool in real time by adopting a visualization method;
4) and under the virtual space, solving the distance between the actual contour and the design contour to evaluate the precision of craniotomy positioning.
In step 1), the orthogonally mapping the lesion model to the scalp design self-adaptive craniotomy contour comprises the following steps:
1.1) constructing a binary mask image conformal to the focus
After the focus and the scalp in the CT image are segmented and three-dimensionally reconstructed, traversing spatial point cloud of a virtual focus model, transforming the spatial point cloud from a world coordinate system to a screen coordinate system through orthogonal mapping, constructing a binary mask image conformal with the focus, and filling tiny holes in the mask image due to point cloud discontinuity by adopting a hole filling algorithm so as to perfect the mask image;
1.2) fast craniotomy positioning based on octree decomposition algorithm
Adopting an octree decomposition algorithm aiming at the scalp model, decomposing the scalp into eight cubes along a minimum bounding box, wherein each cube comprises corresponding point clouds and is sequentially subjected to iterative decomposition in a manner of increasing levels; then, according to the anatomical information of the cranium and the brain, the proper mapping visual angle is adjusted; then, mapping eight vertexes of the cube to a screen coordinate system through orthogonality, judging whether the eight vertexes are in a mask image, if so, keeping the point cloud, otherwise, removing the point cloud, and if the eight vertexes are in the interior, taking high-level sub-nodes of the point cloud to continue iterative operation; finally, a virtual contour which is the same as the mask image is quickly generated;
1.3) contour correction algorithm combined with image morphology to adapt to clinical requirements
And (3) corroding or expanding the edge of the mask image by setting the radius of an operator in the algorithm, repeating the step 1.2), and regenerating the craniotomy contour which meets the surgical requirements.
In step 2), the actual craniotomy contour is drawn on the real craniocerebral scalp, specifically:
the registered surgical tool is shot by an optical surgical navigator, the pose of the surgical tool in the patient space is accurately fed back to the virtual space in real time, the relative position and the deflection angle between the surgical tool and the focus are displayed, auxiliary information for tool adjustment is provided, and a closed contour with the size consistent with the designed craniotomy contour is generated on the scalp when the delineation is finished and the delineation error is caused by improper operation.
In step 3), the recording and displaying of the moving path of the needle tip of the surgical tool in real time by using a visualization method includes: when the operation tool moves, the needle point position of the operation tool is recorded, coordinates of the operation tool are converted into a virtual space after coordinate conversion, the operation tool is displayed in a space point set mode, when the drawing is finished, the needle point of the operation tool returns to the starting point, and all the points are sequentially connected to form a closed contour as a copy of an actual contour.
In step 4), the step of solving the distance between the actual contour and the design contour to evaluate the precision of craniotomy positioning comprises the following steps:
4.1) sampling two virtual contour lines to obtain an actual contour point set CA＝{pi1, …, n and the designed contour point set CD＝{qjAfter 1, …, m, p is obtained by traversing each of the i j valuesiAt CDThe closest point of approach q in (1)k，qkConnection qk-1And q isk+1Obtain the line segment lk-1,kAnd lk,k+1Then solve for piThe shortest distance d to the two line segmentsiFurther form a set D of shortest distancesAD＝{diI | 1, …, n }, and q is obtained in the same wayjTo CASet of shortest distances DDA＝{gj|j＝1,…,m}；
4.2) obtaining the average value d of two groups of shortest distance sets by the following formula (1)meanAs a criterion for the sketching result, thereby evaluating the accuracy of the contour sketching in a standardized manner;
in the formula (d)iIs a set of distances DADN is a distance set DADNumber of elements, gjIs a set of distances DDAM is a distance set DDAThe number of elements.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the invention realizes a self-adaptive craniotomy contour design method, can generate a craniotomy contour with equal size on the surface of the scalp according to the position and the size of a focus, provides a sketching reference for a doctor, and overcomes the defect that the craniotomy contour is designed by staring a three-dimensional focus model with naked eyes in the traditional method.
2. The invention realizes the tracking and positioning of the surgical tool, feeds back the moving path of the surgical tool to the surgical navigation system in real time, and the doctor can adjust the delineation process according to the relative position and deflection angle between the surgical tool and the three-dimensional focus model to finally generate the actual craniotomy contour.
3. The invention provides a standardized examination of craniotomy delineation precision, the indexes can be used as a criterion for delineation precision, and doctors can examine whether the craniotomy delineation result conforms to the originally designed incision or not according to the criterion.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a diagram of the results of lesion-to-scalp segmentation and three-dimensional reconstruction.
Fig. 3 is a mask image of lesion mapping to a screen.
Fig. 4 is a graph of the results of scalp decomposition and storage via octree.
FIG. 5 is a graph of the results after virtual craniotomy contour positioning.
Fig. 6 is a diagram of the effect finally outlined on the actual skull.
Detailed Description
The present invention will be further described with reference to the following specific examples.
As shown in fig. 1, the three-dimensional visualization scalp craniotomy positioning method combined with optical surgical navigation provided by the embodiment includes the following steps:
1) the method comprises the following steps of obtaining a two-dimensional medical image slice from imaging equipment, segmenting a scalp and a focus area in an image, reconstructing the scalp on the surface and reconstructing the focus to construct a three-dimensional model, and specifically comprises the following steps:
1.1) reading a two-dimensional slice image of the cranium and the brain;
1.2) processing the slice image by adopting anisotropic filtering, so that not only is noise information removed, but also edge details are kept;
1.3) rapidly extracting the scalp outline of each slice by using a threshold method according to the CT value of the scalp. The focus is firstly down-sampled to a low-resolution image through an image pyramid algorithm, then image data of the focus is segmented from three dimensions through a Fast Marching algorithm (Fast Marching), and then up-sampled to an image as large as an original image through the pyramid algorithm;
and 1.4) reconstructing image data of the scalp and the focus into three-dimensional model data through a Marching cube algorithm (Marching cube). The model is mainly constructed by triangular meshes which are sequentially connected with point cloud data of specific pixel values, and three-dimensional reconstruction of surface contours of the two points is realized (as shown in figure 2).
2) According to the craniocerebral anatomical information of an actual patient, selecting a proper mapping angle, quickly positioning on the scalp through orthogonal mapping and an octree decomposition algorithm, and designing a craniotomy contour, wherein the craniotomy contour comprises the following specific steps:
2.1) selecting a proper mapping angle in a virtual space through three-dimensional interface interaction, and then transforming all point cloud data to a screen coordinate system by utilizing orthogonal mapping according to a focus three-dimensional model to construct a mask image (as shown in figure 3) with the same size as the point cloud data;
2.2) carrying out octree decomposition on the scalp model, and storing all point cloud information in an octree data structure (as shown in FIG. 4);
2.3) according to the focus area in the mask image, quickly extracting corresponding point cloud on the scalp by using an octree, then reconstructing a curved surface by a triangulation algorithm (Delaunay), and extracting the edge of the curved surface as a craniotomy incision outline (as shown in figure 5).
2.4) according to clinical requirements, the craniotomy needs to be subjected to expansion or reduction correction, the mask image is expanded or corroded, and the step 2.3) is repeated, so that a new incision contour is redesigned.
3) Starting an optical surgical navigation system, finishing surgical tool registration and registration of a patient space and a virtual space, drawing an actual craniotomy on the head of a patient by the surgical tool along a designed virtual contour, simultaneously displaying a moving path of the tool in the virtual space, guiding a doctor to adjust the deflection angle and the position of the surgical tool, and finally generating a new virtual contour. And an accuracy evaluation is performed with the designed profile (as shown in fig. 6).
4) And evaluating the two virtual contours by adopting a standardized precision evaluation method, checking the error of contour delineation, and determining whether the incision design meets the surgical requirements by a doctor according to the evaluation standard. The method comprises the following specific steps:
4.1) sampling two virtual contour lines to obtain an actual contour point set CA＝{pi1, …, n and the designed contour point set CD＝{qj|j＝1,…,m}；
4.2) respectively traversing the two point sets to obtain piAt CDThe closest point of approach q in (1)k，qkConnection qk-1And q isk+1Obtain the line segment lk-1,kAnd lk,k+1Then solve for piThe shortest distance d to the two line segmentsiFurther form a set D of shortest distancesAD＝{diI | 1, …, n }, and q is obtained in the same wayjTo CASet of shortest distances DDA＝{gj|j＝1,…,m}。
4.3) calculating the average value of the shortest distance between the two by the following formula (1) as the standard of the outline drawing precision.
In the formula (d)iIs a set of distances DADN is a distance set DADNumber of elements, gjIs a set of distances DDAM is a distance set DDAThe number of elements.
After the drawing is finished, the doctor follows the standard dmeanJudging whether the delineation error meets the operation requirement or not, and finally guiding the implementation of the craniotomy according to the craniotomy incision with reasonable design.
The above-mentioned embodiments are merely preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, so that the changes in the shape and principle of the present invention should be covered within the protection scope of the present invention.
Claims (4)
1. A three-dimensional visual scalp craniotomy positioning method combined with optical surgical navigation is characterized by comprising the following steps: the method is based on a three-dimensional model of a focus and a scalp, the contour of the focus model is orthogonally projected onto the scalp model according to the minimum principle of surgical injury to generate a self-adaptive craniotomy contour, then the virtual craniotomy contour is sketched to the surface of a real craniotomy brain by combining optical surgical navigation, and the precision of positioning the craniotomy contour is evaluated by means of indexes, and the method comprises the following steps:
1) performing three-dimensional reconstruction according to CT images of the focus and the scalp, rendering the images into a three-dimensional model in a virtual space, and orthogonally mapping the focus model to a self-adaptive craniotomy contour designed on the scalp after selecting an angle of view with small surgical injury through rotating the model;
2) after the registration of the surgical tool and the registration of the patient space and the virtual space are completed by combining an optical surgical navigator, tracking the surgical tool in real time, and drawing an actual craniotomy contour on the real craniocerebral scalp along the virtual craniotomy contour;
3) recording and displaying the moving path of the needle point of the surgical tool in real time by adopting a visualization method;
4) under the virtual space, the distance between the actual contour and the design contour is solved to evaluate the precision of craniotomy positioning, and the method comprises the following steps:
4.1) sampling two virtual contour lines to obtain an actual contour point set CA＝{pi1, …, n and the designed contour point set CD＝{qjAfter 1, …, m, p is obtained by traversing each of the i j valuesiAt CDThe closest point of approach q in (1)k，qkConnection qk-1And q isk+1Obtain the line segment lk-1,kAnd lk,k+1Then solve for piThe shortest distance d to the two line segmentsiFurther form a set D of shortest distancesAD＝{diI | 1, …, n }, and q is obtained in the same wayjTo CASet of shortest distances DDA＝{gj|j＝1,…,m}；
4.2) obtaining the average value d of two groups of shortest distance sets by the following formula (1)meanAs a criterion for the sketching result, thereby evaluating the accuracy of the contour sketching in a standardized manner;
in the formula (d)iIs a set of distances DADN is a distance set DADNumber of elements, gjIs a set of distances DDAM is a distance set DDAThe number of elements.
2. The three-dimensional visual scalp craniotomy positioning method in combination with optical surgical navigation according to claim 1, wherein: in step 1), the orthogonally mapping the lesion model to the scalp design self-adaptive craniotomy contour comprises the following steps:
1.1) constructing a binary mask image conformal to the focus
After the focus and the scalp in the CT image are segmented and three-dimensionally reconstructed, traversing spatial point cloud of a virtual focus model, transforming the spatial point cloud from a world coordinate system to a screen coordinate system through orthogonal mapping, constructing a binary mask image conformal with the focus, and filling tiny holes in the mask image due to point cloud discontinuity by adopting a hole filling algorithm so as to perfect the mask image;
1.2) fast craniotomy positioning based on octree decomposition algorithm
Adopting an octree decomposition algorithm aiming at the scalp model, decomposing the scalp into eight cubes along a minimum bounding box, wherein each cube comprises corresponding point clouds and is sequentially subjected to iterative decomposition in a manner of increasing levels; then, according to the anatomical information of the cranium and the brain, the proper mapping visual angle is adjusted; then, mapping eight vertexes of the cube to a screen coordinate system through orthogonality, judging whether the eight vertexes are in a mask image, if so, keeping the point cloud, otherwise, removing the point cloud, and if the eight vertexes are in the interior, taking high-level sub-nodes of the point cloud to continue iterative operation; finally, a virtual contour which is the same as the mask image is quickly generated;
1.3) contour correction algorithm combined with image morphology to adapt to clinical requirements
And (3) corroding or expanding the edge of the mask image by setting the radius of an operator in the algorithm, repeating the step 1.2), and regenerating the craniotomy contour which meets the surgical requirements.
3. The three-dimensional visual scalp craniotomy positioning method in combination with optical surgical navigation according to claim 1, wherein: in step 2), the actual craniotomy contour is drawn on the real craniocerebral scalp, specifically:
the registered surgical tool is shot by an optical surgical navigator, the pose of the surgical tool in the patient space is accurately fed back to the virtual space in real time, the relative position and the deflection angle between the surgical tool and the focus are displayed, auxiliary information for tool adjustment is provided, and a closed contour with the size consistent with the designed craniotomy contour is generated on the scalp when the delineation is finished and the delineation error is caused by improper operation.
4. The three-dimensional visual scalp craniotomy positioning method in combination with optical surgical navigation according to claim 1, wherein: in step 3), the recording and displaying of the moving path of the needle tip of the surgical tool in real time by using a visualization method includes: when the operation tool moves, the needle point position of the operation tool is recorded, coordinates of the operation tool are converted into a virtual space after coordinate conversion, the operation tool is displayed in a space point set mode, when the drawing is finished, the needle point of the operation tool returns to the starting point, and all the points are sequentially connected to form a closed contour as a copy of an actual contour.
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