Registration of anatomical datasets

Abstract

A computer-aided method for registering data associated with a first data set in a second data set, wherein the method comprises the following steps: Acquisition of an initial data set of an anatomical structure using an image processing device; Development of additional data for the first dataset, wherein the additional data are in a unique identifiable spatial relation to the structure of the first dataset, wherein the additional data include a gravitational vector; Creation of an initial arbitrary reference system for the first data set, wherein the initial reference system is created without reference to a pre-selected orientation point in the structure and the initial reference system is in a unique spatial relationship to the first data set; Acquisition of a second data set of the anatomical structure using an image processing device; Creation of a second arbitrary reference frame for the second data set; Transformation of the first reference frame to the second reference frame by assigning a unique spatial parameter of the first data set to the same unique spatial parameter of the second data set, and Registration of the additional data in the second data set.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention

[0001] The present invention relates to systems and methods for registering anatomical image data sets and for relating anatomical data between anatomical image data sets. 2. Description of the background of the invention

[0002] Various techniques exist for registering patient-related data across different modalities and / or different time periods in computer-assisted surgical procedures. Such patient-related data may include, for example, anatomical data or image data using a variety of image processing techniques or modalities such as ultrasound, magnetic resonance imaging ("MRI"), computed tomography ("CT"), single photon emission computed tomography, positron emission tomography, etc. One technique for registering patient-related data across different modalities is a "point-based" or "pairwise" matching method, whereby landmarks or fiducials that can be identified across different modalities are used to determine a transformation matrix and establish a spatial relationship between the different modalities.In one example, landmarks or fiducials are placed on a patient prior to an image scan, for example, an MRI or CT scan, and such landmarks or fiducials are marked in the image scan and on the patient during a surgical procedure to establish registration between the patient and the patient-related data from the image scan.

[0003] Another method uses surface registration, where multiple surface points of a relevant structure or region are used to create a registration surface. The surface points are labeled independently in different modalities, often using different methods. In one embodiment, the surface registration method is used in ENT surgery, using a patient's face as the registration surface. For example, a CT or MRI scan of the patient's face is created, and the skin surface is labeled in the scan and then assigned to digitized points on the patient's face during the surgery. Such digitized points can be captured either directly with a digitizing device, e.g., a pointer, or indirectly via a registration mask.

[0004] The above registration methods generally serve only to register patient-related data from one modality to another. Typically, during surgery, registration methods register a patient's preoperative image data related to the patient's anatomy in order to locate surgical instruments used to perform the surgery.

[0005] In some types of surgeries, such as those related to musculoskeletal disorders, biomechanical and functional data about joints play an important role in determining the extent or cause of a condition. Such data is typically acquired through motion analysis. In one example of motion analysis, fiducials are placed on the skin of a body part to be analyzed. A navigation system tracks the fiducials while the body part is moved, and the movement of the fiducials is analyzed to create a biomechanical model of the body part. An obvious disadvantage of this technology is that the fiducials are not directly related to the underlying bony structures and that displacement of the skin or soft tissues occurs during movement.Such shifts can contribute to relatively large motion artifacts and inaccuracies in the results of the motion analysis and the created biomechanical model.

[0006] One technique to overcome displacement in soft tissues is the direct implantation of fiducial markers, such as small tantalum beads, onto the patient's bone. These markers are then tracked using stereoradiography techniques as the patient moves the body part. Some of the obvious disadvantages of this technique include the need for surgery to implant the beads and the use of ionizing energy for motion analysis.

[0007] Furthermore, motion analysis during a surgical procedure, when the limb movement is passive, may not adequately capture functional joint data. For example, when a surgeon moves a patient's limbs, or when the patient is anesthetized and lying on an operating table, no voluntary muscle forces are active to counteract the effects of gravity on body mass.

[0008] As surgical procedures for musculoskeletal disorders begin to move away from purely static considerations and toward a more functional assessment of joints and early intervention, the ability to capture functional data related to joints and easily relate this data to the planning and execution of surgical procedures is becoming increasingly important.

[0009] The Wikipedia entry "Image registration," URL: https: / / de.wikipedia.org / w / index.php?title=Bildregistrierung&oldid=76480840 (version from July 9, 2010), explains that image registration is an important process in digital image processing and is used to align two or more images of the same scene, or at least similar scenes, as closely as possible. One of the images is designated as the reference image, and the others are the object images. A transformation is then calculated that optimally adapts the object images to the reference image. The images to be registered differ from one another because they were taken from different positions, at different times, or with different sensors. Image registration methods are particularly common in medical image processing.There, images acquired with different imaging techniques (modalities) are aligned. Furthermore, various area-based and feature-based methods for feature alignment, as well as various models for calculating transformations, are described. SUMMARY OF THE INVENTION

[0010] According to aspects of the present disclosure, computer-assisted methods for data registration, computer-assisted methods for spatial data association, systems for acquiring and processing a volume dataset of an anatomical structure, and a method for establishing a position of a portion of a bone are provided according to the independent claims. Preferred embodiments are specified in the dependent claims.

[0011] According to some aspects, a computer-assisted method for registering data associated with a first data set to a second data set is disclosed. The method comprises the steps of acquiring a first data set of an anatomical structure with an image processing device, developing additional data for the first data set, the additional data having a uniquely identifiable spatial relationship to the structure of the first data set, and establishing a first arbitrary reference frame for the first data set. The first reference frame is established without reference to any preselected landmark in the structure, and the first reference frame has a unique spatial relationship to the first data set.The method also includes the steps of acquiring a second data set of an anatomical structure with an image processing device, creating a second arbitrary reference frame for the second data set, and transforming the first reference frame to the second reference frame by assigning the same unique spatial parameter of the second data set to each unique spatial parameter of the first data set and registering the additional data in the second data set.

[0012] According to other aspects, a computer-assisted method is disclosed for associating spatial data associated with a first volume dataset of an anatomical structure with a second volume dataset of the anatomical structure. The method comprises the steps of acquiring a first volume dataset of the anatomical structure with a computer-assisted surgical navigation system, assigning a first arbitrary reference frame to the first volume dataset, calculating an inherent property of the first volume dataset, correlating the inherent property with the first arbitrary reference frame, and associating additional spatial data with the first volume dataset.The inherent feature has a unique position and orientation relative to the anatomical structure that can be identified from any reference position, and the additional spatial data has a unique spatial relationship correlated with the first arbitrary reference frame. The method further comprises the steps of acquiring a second data set of the anatomical structure with a computer-assisted surgical navigation system, assigning a second arbitrary reference frame to the second data set, identifying the inherent feature in the second data set, and correlating the inherent feature with the second arbitrary reference frame.The method also includes the steps of registering the first volume dataset with the second volume dataset based on the inherent property, correlating the additional spatial data with the second dataset upon registration thereto, and displaying the additional spatial data registered in the second dataset on a display device. The registration step is performed by a computer.

[0013] According to further aspects, a system for acquiring and processing a volume dataset of an anatomical structure comprises means for acquiring a first volume dataset of an anatomical structure of a patient and a second volume dataset of the anatomical structure, and means for calculating an inherent property of the first volume dataset and the second volume dataset. The inherent property has a unique position and orientation relative to the anatomical structure that can be identified from any reference position.The system further comprises means for assigning a first arbitrary reference system to the first volume data set and a second arbitrary reference system to the second volume data set, means for correlating the inherent property with the first arbitrary reference system and means for associating additional spatial data with the first volume data set, the additional spatial data having a unique spatial relationship correlated with the first arbitrary reference system, the system also comprises means for registering the first volume data set with the second volume data set based on the inherent property and means for correlating the additional spatial data with the second volume data set upon registration therein.

[0014] According to further aspects, a method for determining a position of a portion of a bone that has been altered from a normal shape comprises the step of acquiring a first volume data set for a first bone that is unaltered, the first volume data set comprising volume data for the first and second portions of the first bone. The method also comprises the steps of identifying a first unique spatial feature of the volume data for the first portion of the first bone, establishing a first arbitrary reference frame for the first volume data set correlated with the first unique spatial feature, and identifying a unique spatial relationship between the first arbitrary reference frame and the second portion of the first bone.The method further comprises the step of identifying a second bone which normally mirrors the first bone about a central axis, the second bone comprising a first part and a second part which substantially correspond as mirror structures to the first and second parts of the first bone, respectively, and the second bone has been altered from a normal shape such that the first part of the second bone is in an altered position relative to the second part of the second bone.The method further comprises the steps of acquiring a second volume data set of the first part of the second bone, identifying a second unique spatial feature of the second volume data set, the second unique spatial feature substantially mirroring the first unique spatial feature, registering the first volume data set in mirrored correlation with the second volume data set by correlating the first unique spatial feature with the second unique spatial feature, and restoring the normal position of the second part of the second bone corresponding to the position of the second part of the first bone with respect to the registered position of the first part of the first bone.

[0015] Further aspects and advantages of the present invention will become apparent upon consideration of the following detailed description. A BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a schematic representation of one embodiment of a surgical navigation system adapted to implement the methods of the present invention; The Fig. 2 and Fig. 2a are flowcharts of registration methods according to the present invention; The Fig. 3A, Fig. 3B and Fig. 3C shows the development of additional spatial data for an anatomical structure, represented on a first dataset and the relation of this data to a second dataset; Fig. 4A is an example screenshot and Fig. 4B and Fig. 4C are visual representations illustrating data collection and registration; Fig. Figure 5 shows the development of additional spatial data for a first anatomical structure and the relation of this data to a second anatomical structure that reflects the first anatomical structure; The Fig. 6A and Fig. 6B show an example of a preoperatively defined anatomical reference system that is not accessible during a surgical procedure and The Fig. 7A and Fig. 7B show an example of the determination of functional movement parameters of a patient’s hip, A DETAILED DESCRIPTION OF THE DRAWINGS

[0016] The systems and methods of the present invention can be used to register various data sets associated with one or more structures of a patient and / or to relate additional data from one such data set to another such data set, where the additional data may not be available or practically impractical for the other data set. In many cases, positional data from non-contiguous regions of the body are linked together without the need to identify local anatomical reference systems or to refer to them based on predefined anatomical landmarks. In one application, functional data from one data set is related to another data set to facilitate performing a functional assessment of a structure.For example, the structure may be an anatomical structure, such as a bone or joint of a patient, and the volume dataset may be an image dataset of the bone or bones acquired using an ultrasound probe or other known image processing technique or other known modalities. The functional data developed for the anatomical structure from a preoperative image dataset may be related to an intraoperative image dataset to assist in the planning and execution of surgical procedures or to facilitate the early detection and prevention of certain diseases or harmful conditions. In a further embodiment, other data may also be used, for example, to reconstruct an anatomical reference system that is available in one dataset but not in another.Another aspect of the present invention is the ability to register different data sets to a structure without requiring predefined landmarks or fiducials in the structure. Instead, arbitrary reference systems are created for different data sets and used to register such data sets.

[0017] Now to the drawings. Fig. 1 is a schematic representation of a surgical navigation system 20 adapted to perform the steps of the method(s) disclosed herein. The surgical navigation system 20 includes a display unit 22, a computer system 24, and a camera assembly 26. In the present embodiment, the computer system 20 is housed in a movable cart 28. The computer system 24 may, for example, be any type of computer having a storage unit, a processor, and memory (all not shown), as would be apparent to one of ordinary skill in the art. The display unit 22 may be any conventional display usable with the computer system 24, such as a standard computer monitor or television. An example of a surgical navigation system is the Stryker Navigation System, available from Stryker Corporation.

[0018] The surgical navigation system 20 is adapted to acquire image data of a patient 30. In one embodiment, the image data is acquired by an ultrasound probe 32, processed by a user 34, such as a surgeon or nurse, and transmitted wirelessly to the computer system 24. Alternatively or additionally, a system may be used that uses cables for data transmission between the ultrasound probe 32 and the computer system 24. In the present embodiment, the ultrasound probe 32 represents a non-invasive, non-ionizing, and portable imaging method for acquiring image data of the patient 30. Furthermore, the ultrasound probe 32 provides image data of the underlying bones to avoid motion artifacts due to skin displacement.However, in other embodiments, image data may also be acquired using any other imaging technique or acceptable modalities, such as magnetic resonance imaging (“MRI”), computed tomography (“CT”), single photon emission computed tomography, positron emission tomography, and the like.

[0019] The camera assembly 26 is adapted to detect the position of a sensor 36 coupled to the ultrasound probe 32 in order to track the position and orientation of such ultrasound probe 32. As non-exclusive examples, the sensor 36 may be comprised of one or more light-emitting diodes ("LEDs"), the camera assembly 26 may include a first camera 38, a second camera 40, and a third camera 42, and the first, second, and third cameras, namely 38, 40, 42, may be three CCD cameras adapted to detect infrared ("IR") signals generated by the sensor 36. Although not shown here, the user 34 may employ other surgical devices and instruments adapted to be tracked by the camera assembly 26 in the same manner as the ultrasound probe 32.These additional surgical devices and instruments may have sensors 36, such as light-emitting diodes, either built into the device or instrument or physically connected thereto in a known or determinable position and orientation sufficient to track the position of the instruments.

[0020] The camera assembly 26 is mounted on a rotatable arm 44 attached to the movable carriage 28 so that the camera assembly 26 has sufficient line of sight to a relevant area where a procedure will be performed. In other embodiments, the camera assembly 26 may be mounted on a wall of an operating room (not shown) or at another suitable surface or location.

[0021] The surgical navigation system 20 may be an active optical system that includes at least one infrared transmitter and receiver used to transmit data to and from the sensor 36. For example, in the present embodiment, the camera assembly includes a first transmitter and receiver 46 and a second transmitter and receiver 48 mounted separately from each other. Although the present invention is described as using an active optical surgical navigation system, the systems and methods of the present invention may also be used with other surgical navigation technologies and systems, such as passive optical systems, magnetic systems, inertial navigation systems, and the like. Other computer-assisted systems may also be used, including RFID-based systems, video imaging systems, and the like.

[0022] The camera assembly 26 is connected via a cable 50 to a localizer (not shown) or, in some cases, directly to the computer system 24. The localizer cooperates with the camera assembly 26 to identify the location and orientation of the sensor 36 on the ultrasound probe 32 within the line of sight of the camera assembly 26. In one embodiment, the localizer converts raw position data from a plurality of LEDs comprising the sensor 36 into the orientation of the individual LEDs and then transmits this data to the computer system 24. In another embodiment, the localizer converts raw position data from the LEDs into the position and orientation of the ultrasound probe 32 and then transmits this data to the computer system 24. In a further embodiment, a software program executed by the computer system 24 can convert the raw data into the orientation of the ultrasound probe 32.The conversion of the raw position data is well known to those skilled in the art. Computer system 24 can optionally be controlled remotely using control buttons (not visible) on ultrasound probe 32 or at another location easily accessible to user 34. Computer system 24 also includes one or more input devices such as a keyboard 52, a mouse 54, or any other input device for operating computer system 24.

[0023] Next, with reference to the Fig. 2 and Fig. 2a discloses methods for registering a first volume dataset of an anatomical structure with a second volume dataset of the anatomical structure. The methods are preferably implemented using a computer-assisted surgical navigation system as described herein, wherein the navigation system can track the position of one or more devices to acquire volume datasets, store and extract position data therefrom, and correlate the position data with the volume datasets.

[0024] Fig. Figure 2 provides a broad overview of a method for registration in which control begins at block 80, which acquires a first data set for a structure, such as an anatomical structure of a patient. After block 80, control transfers to block 82, which develops additional positional data related to the first data set, and to block 84, which determines or creates a first reference frame for the first data set. The first reference frame is preferably any reference frame, block 86 acquires a second data set, and block 88 creates a second reference frame for the second volume data set. Control then transfers to block 90, which transforms the first reference frame into the second reference frame, and to block 92, which relates the additional spatial data from the first reference frame, such as functional data about the anatomical structure, to the second reference frame.

[0025] Fig. Figure 2A describes a more detailed view of a method in which the method of Fig. 2, wherein control begins at block 100, which acquires a first data set for a structure, such as an anatomical structure of a patient. The first data set may include a first volume data set for the anatomical structure. As used herein, the term "anatomical structure" may encompass an entire anatomical structural unit, such as an entire bone, or the term "anatomical structure" may encompass a smaller portion of the entire anatomical structural unit, less than the whole, such as only a small portion of the bone. Preferably, the volume data set includes data regarding the position and orientation of the anatomical structure, such as a bone or a joint. The first volume data set is acquired with a subcutaneous imaging device, such as the tracked ultrasound probe 32 in Fig. 1, wherein the volume dataset includes an image of a bone or other subcutaneous structure of a patient. Other image acquisition devices and modalities may also be used to acquire the first image dataset, such as CT, MRI, X-ray, etc. The first volume dataset may, for example, be acquired preoperatively. The first volume dataset preferably includes image data about the anatomical structure and may include two-dimensional (2D) image data and / or three-dimensional (3D) image data. An example of an acquisition device and modality for acquiring the first image dataset includes a 2D or 3D ultrasound imager; when a 2D ultrasound probe is used, this probe may be used to acquire volume data by acquiring multiple slices of a region to which the anatomical structure belongs.During acquisition of the volume dataset, the position of the acquisition device is tracked by the surgical navigation system. Preferably, the anatomical structure is in a stable position while the volume dataset is acquired, eliminating the need to separately track the position of the anatomical structure during acquisition. The anatomical structure can optionally be tracked during acquisition, in which case the anatomical structure is allowed to move during acquisition, and / or the position data for the acquired volume dataset containing the anatomical structure can be additionally corroborated.

[0026] After block 100, control transfers to block 102, which assigns or determines a first reference frame for the first data set. The first reference frame is preferably an arbitrary reference frame without reference to a predefined landmark, such as a fiducial or a particular anatomically prominent point in the anatomical structure. For example, the first reference frame may be that of a camera array, an ultrasound probe, or the first volume data set itself, such as a center of the first volume data set. Other ways of creating the arbitrary reference frame so that it differs from other types of reference frames may also be used. The reference frame may be created using any known or commonly used image processing algorithm.Once created, the arbitrary reference frame preferably has a unique spatial relationship to the volume of the anatomical structure in question, such as a bone, and the arbitrary reference frame remains fixed in the same position relative to it.

[0027] Control transfers to block 104, which identifies an inherent property of the first volume data set, such as a spatially unique physical spatial aspect of the volume data set. Preferably, the inherent property has a unique position and orientation relative to the anatomical structure that can be identified from any reference position. In a preferred method, the computer system 24 is adapted with appropriate command routines to calculate an image moment of inertia of the volume data set that is constant with respect to the volume, regardless of the angle from which the volume is acquired or viewed.The use of moment of inertia can be advantageous because any given volume has a constant moment of inertia that stands in a unique, fixed spatial relationship to a dataset representing a particular volume and is independent of the viewpoint from which the volume is viewed. Therefore, for example, the moment of inertia of a volume dataset of a particular portion of a bone will remain in the same relative position to that portion of the bone, regardless of the position or viewpoint from which the volume dataset is acquired. Other methods for determining a spatially unique physical spatial aspect of the volume dataset may also be used and capture alternative or additional uniquely defined spatial data about the anatomical structure, such as surface contour data, landmarks, etc., which could be used to define the arbitrary reference frame.

[0028] Control then transfers to block 106, which correlates the first arbitrary reference frame with the spatially unique physical aspect of the volume data set. In one example, block 108 correlates the first arbitrary reference frame and the image moment of inertia using a known unique spatial relationship between them, such as the Cartesian xyz coordinates of the image moment of inertia within the first arbitrary reference frame. In one example method, the first arbitrary reference frame is assigned such that the moment of inertia defines an axis of the arbitrary reference frame. Other alternative and / or equivalent methods or systems for correlating the arbitrary reference frame with the spatially unique physical aspect may be used.

[0029] Control transfers to block 108, which develops and / or associates additional positional data with the first volumetric data set, wherein the additional spatial data has a unique spatial orientation relative to the first arbitrary reference frame. The additional positional data may include functional data of the anatomical structure, such as a gravity vector affecting the anatomical structure and / or the orientations of parts of the anatomical structure relative to every other part. In one embodiment, the first data set is a pre-operative volumetric data set, and the functional data is acquired for the anatomical structure while a patient is in a generally standing or upright position. In other embodiments, the functional data may also be acquired using other methods known to those skilled in the art.

[0030] The additional spatial data may be associated with the first volume data set. For example, the additional spatial data may include gravity vector data defining a gravity vector on the first volume data set at the time the volume data set was acquired. The gravity vector may be determined using any known method. One such method includes a gravity measuring device, such as an accelerometer, mounted on the camera of the surgical navigation system, wherein the gravity measuring device identifies the local gravity vector while the first volume data set is being acquired. The gravity vector data is then associated with the volume data set such that the gravity vector can be unambiguously located with respect to the first arbitrary reference frame.

[0031] In another example, the additional spatial dataset is unrelated to the first volume dataset. For example, the additional spatial data may include a vector that specifies the location and orientation of another reference system. The other reference system may be another arbitrary reference system for an unrelated volume dataset that does not overlap with the first volume dataset, where the unrelated volume dataset relates to a different anatomical structure or a different part of the same anatomical structure. In one case, the first volume dataset may be the first part of a bone and the unrelated volume dataset may be a second part of the same bone. The other reference system may also include a global reference system that belongs to multiple volume datasets, such asa camera reference system from a camera of the surgical navigation system. In this way, the specific locations and / or orientations of the reference systems of each of one or more non-contiguous volume data sets can be linked to the first volume data set such that the location and orientation of one or more of the volume data sets can be used to determine the location and orientation of one or more other non-contiguous volume data sets, even though the volume data sets do not specifically overlap and are not visible at that time.

[0032] Other types of additional spatial data that may have unique spatial properties related to the anatomical structure represented by the volume dataset may also be identified with the volume dataset. As non-exclusive examples, other types of additional spatial data could include location and orientation vector(s) of the arbitrary reference frame of the volume dataset with respect to other local anatomical reference frames of the patient, e.g., a pelvic plane, a mechanical axis of the femur, an anatomical axis of the femur, and other relevant local landmarks and / or reference frames as commonly used.However, it is assumed here that any type of spatial data that has a uniquely identifiable spatial feature related to the anatomical structure represented by the volume dataset can be linked to the volume dataset as deemed necessary or appropriate for a variety of different applications.

[0033] Control transfers to block 110, which acquires a second data set. In one example, the second volume data set may belong to the same anatomical structure as the first volume data set or at least have significant overlap with it. There is sufficient overlap between the first data set and the second data set such that the first and second data sets can be registered in a subsequent step, as described below. In a preferred embodiment, there is at least a seventy percent match of the anatomical structure acquired in the first volume data set with the anatomical structure acquired in the second volume data set. In some cases, even more than seventy percent match may be desirable, and in other cases, less than seventy percent match may be sufficient.The second volume dataset can be acquired from the same angle as the first volume dataset, or it can be acquired from a different angle.

[0034] In another example, the second volume dataset may be from a different anatomical structure that has a known or determinable spatial relationship to the first anatomical structure. In one aspect, the first volume dataset may be from a bone or portion thereof on one side of a patient's body, and the second volume dataset may be from a bone or portion thereof on the opposite side of the patient's body that is substantially a mirror image of the first bone. As a non-exclusive example, the first volume dataset may include image data from a left femoral head, and the second volume dataset may include image data of the right femoral head. The left femoral head is assumed to be mathematically equivalent to a mirror image of the right femoral head mirrored about a central axis of the body.In this way, the left femoral head and the right femoral head have a known or determinable spatial relationship to each other across the midline of the body. For example, a known standard anatomical feature of the femoral head, such as the lesser trochanter, can be designated as a landmark, assuming that it is located at the same location on the left and right femurs, only mirrored across a midline of the body. Other recognizable relationships between different anatomical structures can also be identified and used in a similar manner to that described here.

[0035] In some applications, the second volume dataset is acquired during a different part of a procedure than the first volume dataset, for example, intraoperatively. In one example, the second dataset is an intraoperative volume dataset of the same bone or a portion of it, acquired while the patient is anesthetized and lying on an operating table. In other applications, the first and second volume datasets could be acquired during the same portion of a surgical procedure, for example, both intraoperatively or both preoperatively. In addition, one or more volume datasets may be acquired postoperatively, such as to assist with postoperative diagnostics.

[0036] The second data set may be acquired using the same modality or a different modality than the first data set. In one example, both the first and second data sets are acquired using a 3D ultrasound imaging system attached to a tracking device that is tracked by the surgical navigation system. In the present example, the second data set is also acquired using ultrasound probe 32, which is tracked by the surgical navigation system 20.

[0037] Control then transfers to block 112, which assigns a second reference frame to the second data set. As with the first reference frame, the second reference frame may be an arbitrary reference frame and assigned or determined in a similar manner as described therein. The second arbitrary reference frame is preferably uniquely defined by the second volume data set. In one example, the second arbitrary reference frame is defined by the anatomical structure in the same manner as described hereinbefore with respect to the first anatomical structure. The second reference frame may be the same as or different from the first reference frame.

[0038] Control also transfers to block 114, which identifies an inherent property of the second volume data set, such as a spatially unique physical spatial aspect of the volume data set. If the first and second data sets are from substantially the same anatomical feature, the inherent property of both data sets should preferably be the same because the same anatomical feature would have the same unique spatial aspect for the first and second data sets, such as image moment of inertia. For example, in a system that calculates an image moment of inertia of an ultrasound image, the moment of inertia of the structure is constant and substantially unique with respect to a given structure regardless of the viewpoint from which the structure is viewed.Therefore, the moment of inertia of the same anatomical feature is uniquely identifiable in different volume datasets of the anatomical feature acquired from different viewpoints. In such an example, the second arbitrary reference frame can also be uniquely spatially related to the image moment of inertia.

[0039] Block 116 correlates the second reference system with the inherent feature of the second volume data set in the same manner as in block 106 or with any method sufficient thereto.

[0040] Control then transfers to block 118, which registers the first reference frame with the second reference frame. In one embodiment, block 118 performs a mapping of the data sets, for example, by searching for the unique moment of inertia of each image and correlating the first and second arbitrary reference frames with each other by mapping the moment of inertia of the first volume data set to the moment of inertia of the second volume data set and calculating a suitable transformation matrix therefrom. Another way to map data sets may involve performing different mappings for the first and second data sets, wherein the first and second data sets are virtually overlaid and correlated with each other using any suitable or well-known method.Registration may also be performed using other methods, such as volume-to-volume mapping, surface-to-surface mapping, and / or point-to-point mapping. In each registration technique, a mathematical transformation, including rotation, translation, and scaling, is computed, preferably by the computer system 24, that registers a common or assumed-to-be-common spatial feature in the two volume data sets. The computer system 24 then converts one or both of the arbitrary reference frames such that the spatial feature, and thus the volume data sets, are registered with each other. Other equally effective methods for calculating and performing an appropriate transformation and registration, known to those skilled in the art, may also be used.

[0041] Control then transfers to block 120, which relates the additional spatial data from the first reference frame, such as functional data of the anatomical structure, to the second reference frame. The additional spatial data from the first volume data set is related to the second arbitrary reference frame of the second volume data set after (or simultaneously with) the registration of the first and second data sets. In this way, the additional spatial data is correctly registered to the second arbitrary reference frame, even though the additional spatial data is not immediately available when the second volume data set is acquired.For example, if the additional spatial data, as described above, includes the gravity vector, the gravity vector will be associated with the second volume dataset and registered in the correct orientation to the anatomical structure, even if the anatomical structure is oriented differently. If the additional spatial data, as described above, includes a vector that identifies the location and orientation of another reference frame, then the location and orientation of the unrelated volume dataset that is not part of the second volume dataset can be identified based on the association and registration of the vector data that constitute the additional spatial data.

[0042] Optionally, control can then be passed to block 122, which displays the registration with the second volume data set on a display device. Further modifications and uses of the additional spatial data can also be performed as desired.

[0043] The blocks 100-122 described above may be rearranged, reordered, or modified by combining them to include fewer steps or by decomposing them to include further additional steps, as would be apparent to one skilled in the art. As in Fig. As shown in Figure 2A, steps 100-122 correlate in some cases with the Fig. 2, which can be considered as their intermediate steps. Furthermore, the logic shown in the flowcharts of Fig. 2 and Fig. 2A, may be implemented by any computer system adapted to perform blocks 80-92 and / or 100-122, such as the surgical navigation system 20 of Fig. 1. In one embodiment, the computer system 24 comprises appropriately programmed software and hardware to implement the blocks and processes of the Fig. 2 and Fig. 2A to be carried out.

[0044] The Fig. 3A, Fig. 3B and Fig. 3C show an example where the additional spatial data includes functional data for an anatomical structure obtained from a preoperative volumetric data set and related to an intraoperative volumetric data set so that the functional data can be used during a surgical procedure on the patient. During such a surgical procedure, for example, a hip arthroplasty, a gravitational vector affecting the various bones that make up the hip joint may be an important factor for the precise positioning of components of a prosthetic hip implant due to certain functional movement characteristics of the patient. In other embodiments, functional data for the anatomical structure may be acquired in a variety of different positions or over an extended period of time.For example, functional data for a knee joint can be collected in different positions to include extension / flexion and varus / valgus data for use during a surgical procedure.

[0045] During hip arbitrary surgery, a prosthetic component is precisely and efficiently placed using the arbitrary reference frame described here, rather than relying on local biomechanical / anatomical reference frames, such as a mechanical axis of the femur, a pelvic coronal plane, or other standard local anatomical reference frames. The term "local" reference frame, as used herein, refers to a reference frame based on certain accepted or predefined anatomical features of a patient, such as specific skeletal landmarks. In contrast, the term "arbitrary reference frame" refers to a reference frame that is uniquely identified based solely on the feature under consideration, such as the specific volumetric data set under consideration.Thus, the arbitrary reference system does not depend on the location of one or more specific predefined anatomical landmarks with respect to other parts of the anatomy, but correlates with and is identifiable from unique spatial characteristics of the relevant anatomy itself.

[0046] The association of functional data, such as the gravity vector G, with the intraoperative procedure facilitates the placement of the correct prosthetic components in an optimal position and orientation based on the patient's natural movement patterns. The position and orientation of the prosthesis can be further optimized using a variety of parameters, including, for example, specific anatomical and kinematic constraints, specific activities inherent in the patient's lifestyle, and certain geometric and kinematic constraints due to the prosthetic design. Further improvements are possible by incorporating other relevant factors that arise or become apparent intraoperatively, such as after the creation of a common surface to accommodate a prosthetic component.

[0047] Fig. Figure 3C shows steps in a method and a specific example that utilizes additional spatial data on a computer-assisted surgical navigation system, such as the surgical navigation system 20, including the functional data related to the Fig. 3A and Fig. 3B. Block 170 acquires a preoperative image volume dataset 150 of a hip 152 or portions of the patient's hip 154 ​​while the patient is standing. Preferably, the image volume dataset 150 is acquired with the ultrasound probe 32 while being tracked by the camera assembly 26 to acquire image data of the relevant bones in the hip joint, and the image data is stored in suitable electronic memory available to the surgical navigation system.

[0048] Block 172 defines an arbitrary axis, such as a camera array axis, for the image volume dataset 150, identifies a unique spatial parameter of the image volume dataset, and correlates the arbitrary axis with the spatial parameter. In this particular example, the unique spatial parameter preferably comprises the image moment of inertia of the image volume dataset of the hip bones, calculated as previously described herein. The arbitrary axis is optionally also correlated with a local anatomical parameter of the hip 152, such as a frontal plane 156 of the hip 152, as in Fig. 3 shown.

[0049] Block 174 assigns additional spatial data to the image volume data set 150, including functional data such as a gravity vector G. In this example, the gravity vector G is represented as being relative to the hip 152 in Fig. 3A points downward toward the floor because the patient is upright while the image volume dataset 150 is acquired. The gravity vector is acquired using an inertial system with an accelerometer, but it may be acquired by any sufficiently known system, such as a level measurement system or other systems. The gravity vector G is spatially assigned by determining an orientation of the gravity vector G with respect to the anatomical parameter and / or an arbitrary axis, such as a particular inclination angle β to the frontal plane 156. In further examples, other anatomical parameters may be defined, for example, a functional plane 158, an iliac crest, a pubic symphysis, and the like, and thereby defining various planes and angles, wherein the gravity vector G may be related to such anatomical parameters.

[0050] Block 176 acquires an intraoperative image volume dataset 160 of the same general area while the patient 154 is in a general prone position in a manner similar to block 170.

[0051] Block 178 performs a data comparison to register the preoperative image volume data set 150 and the intraoperative image volume data set 160 using a suitable data matching method, such as image moment of inertia matching or the previously described volume data matching methods. Through this registration, the gravity vector G is simultaneously or later transferred to the intraoperative data set 160 for use during the procedure.

[0052] Block 180 displays the image volume data set 160 on the display unit 22 with the gravity vector G registered with the bones of the hip. A replacement prosthesis can then be aligned with the bones of the hip via the surgical navigation system 20 in relation to the bones preselected based on the bones' position relative to the gravity vector.

[0053] The information relating to the Fig. 3A-3C is preferably implemented by the surgical navigation system 20, and blocks 172, 174, 178, and 180 are preferably performed by corresponding computer software routines associated with and controlling the computer system 24, preferably by any available method known to those skilled in the art.

[0054] The Fig. 4A-4C show an example of a volume dataset mapping registration method, showing three data acquisition screens. In a first step, a preoperative volume dataset 190 from a patient's hip is acquired with an ultrasound probe and displayed on a screen, as shown in Fig. 4A, and assigned a first arbitrary reference frame 192. Optionally, additional spatial data, such as a gravity vector G, is associated in a unique spatial location with respect to the volume data set 190. Then, an intraoperative volume data set 194 of the hip is acquired and assigned a second arbitrary reference frame 196. In the present example, the anatomical parameter of the hip includes a right iliac crest 198, a left iliac crest 200, and a pubic symphysis 202 in the preoperative volume data set. The same right and left iliac crests and pubic symphysis are also identified in the intraoperative volume data set 194, whereby such structures in the preoperative and intraoperative volume data sets may form a unique arbitrary reference frame for the data sets.Additionally or alternatively, the image moment of inertia is calculated for each of the preoperative and intraoperative volume data sets 190 and 194 such that the image moment of inertia of the preoperative volume data set 190 is equal to or sufficiently similar to the image moment of inertia of the intraoperative volume data set 194. Preferably, there is an overlap of approximately seventy percent or more between the two volume data sets 190 and 194. Fig. Figure 4B shows the preoperative volume data set 190 and the intraoperative volume data set 194 of the hip, which overlap prior to registration, as in the first and second matched arbitrary reference frames 192 and 196, which are not registered. The preoperative data set 190 and the intraoperative data set 194 are then registered by a reference frame transfer by superimposing and correlating the reference frames of the respective data sets, as in Fig. 4C, which shows the pre- and intraoperative volume datasets 190 and 194 of the hip overlapping after registration. After the pre- and intraoperative volume datasets are registered, the transformation between the datasets is used to relate the additional spatial data, such as the gravity vector, from the pre-operative volume dataset 190 to the intraoperative volume dataset 194. As stated above, the gravity vector G is determined with respect to an anatomical parameter of the hip in the pre-operative volume dataset and assigned to the volume dataset in a unique spatial orientation thereto.

[0055] The design of the Fig. Figures 3A-3C and 4A-4C offer an improvement over previous surgical procedures, which typically used the functional plane 158 as an approximation for the gravitational vector G. The functional plane 158 can be determined using known methods, for example, by identifying an anterior superior iliac vertebra and by integrating longitudinal body axes. Although the functional plane 158 provided a fairly good approximation of the gravitational vector, there is typically a difference of approximately 5° to approximately 10° between the orientation of the functional plane 158 and the gravitational vector. Therefore, determining and assigning the gravitational vector G is a much more accurate and reliable method for considering functional aspects of the patient with normal activity and movement parameters.

[0056] The concepts described here can also be used in orthopedic, reconstructive, or trauma surgery procedures where it is important to restore the function and anatomy of an affected area. In some cases, an unaffected area is used to mirror an affected area in order to obtain symmetrical biomechanical parameters, such as spatial relationships, angles, and biomechanical parameters, to restore the affected area. For illustrative purposes only. Fig. 5, image data and functional data for a patient with a fractured left femur can be obtained for a healthy right femur. The functional data for the right femur can be obtained using the method of Fig. 2 to the fractured left femur in order to obtain symmetrical biomechanical parameters for the reconstruction of the fractured left femur. In this example, the data sets for the right and left femurs are typically acquired intraoperatively due to the circumstances of typical trauma surgery, as would be obvious to a specialist in this field.

[0057] In the example from Fig. 5 shows a schematic image dataset 210 of a left femur 212 and a right femur 214. The left femur 212 has sustained trauma, namely a severe fracture 216 across the femoral neck and a separation of the left femoral head 218, while the right femur 214 is unaffected. The image dataset 210 can be acquired in a single operation using any suitable modality, such as the ultrasound probe 32 and the surgical navigation system 20, as described above, and stored in the computer system 24. The computer system 24 then develops data for the left and right femurs 212 and 214 from the image dataset 210. The data includes a first volume dataset 220 including the left femoral head 218 and a second volume dataset 222 including a portion of the left femoral body 224.The volume data sets 220 and 222 are preferably non-adjacent to each other and / or mathematically isolated from each other on opposite sides of the fracture 216. The data also includes a third volume data set 226 containing the healthy right femur 214. The third volume data set 226 includes a volume data set 228 of the femoral head of the right femur 214 and an unrelated volume data set 230 of a portion of the right femur body. The right femur 214 is preferably held immobile throughout the acquisition of the data set 226, including the volume data sets 228 and 230.Alternatively, a tracking device (not shown) may be attached to the femur 214 while the volume data set 226 is being acquired to corroborate the position data of the volume data sets 228 and 230 relative to each other and / or to correct the movement of the right femur during the acquisition of the volume data set 226.

[0058] Each volume data set 220, 222, 228, and 230 is assigned an arbitrary reference system 232, 234, 236, and 238, respectively. Each reference system 232, 234, 236, and 238 preferably has a location and orientation that correlates with a uniquely identifiable aspect of the volume data set, such as the image moment of inertia described herein.

[0059] Additional spatial data is created, forming a vector 240 that uniquely defines the spatial relationship, including position and orientation, of the volume data sets 222 and 230 to one another. Thus, the reference frames 236 and 238 are spatially correlated by the vector 240 in a global reference frame 242, such as the camera array 26, even though the two volume data sets are not related to one another. Of course, other global reference frames may also be used. The calculation of the additional vector 240 may not be required or may serve to provide additional mathematical support by providing redundant measurements, for example, if the volume data set 228 is not related to the volume data set 230.

[0060] Next, the first volume data set 220 and the second volume data set 222 of the affected left femur 212 are associated with each other and registered with the corresponding portions 228 and 230, respectively, of the third volume data set 226 of the right unaffected femur 214 to determine a reconstructed position of the left femoral head 218 and the left femoral body 224 that correspond to the corresponding portions of the right unaffected femur 214. In one example method, the registration process includes transferring a reference frame of the right unaffected femur 214 to the reference frame of the volume data sets 220 and 222 of the affected left femur 212.For this purpose, it is assumed that the shape and position of the left femur 212 is an identical mirror image of the shape and position of the right femur 214, mirrored about a central axis between them. It is assumed that the shapes of the parts of the right femur 214 captured in the volume data sets 228 and 230 substantially correspond to the shapes of the corresponding parts of the left femur 212 captured in the volume data sets 220 and 222, respectively. Under these assumptions, the reference systems 236 and 238 and the corresponding volume data sets 228 and 230 and the vector 240 of the right femur 214 are mathematically mirrored about a central axis 244 so that they are aligned to coincide with the left femur 212.One of the volume data sets 220 or 222 of the left femur 212 is then mapped to the corresponding mirrored volume data set 228 or 230 of the right femur 214. For example, the volume data sets 222 and 238 may have an easily identifiable three-dimensional feature, such as the lesser trochanter 246, which can be used to register the volume data set 222 with the mirrored volume data set 238. In another example, an image moment of inertia is calculated for the two volume data sets 222 and 238, and the image moments of inertia are then mapped to each other after mirroring the right femur data. Other methods for registering mirrored corresponding volume data sets may also be used.

[0061] After the volume data set 222 has been registered with the mirrored volume data set 238, data about the orientation of other parts of the unaffected right femur 214 to the affected left femur 212 can be related and used by a surgeon to correctly position the fragments of the affected left femur 212. For example, the mirrored vector 240' and the volume data set 228 define the theoretically correct position of the left femoral head 218 with respect to the left femoral body 224. Preferably, the tracking devices 246 and 248 are attached to the left femoral body 224 and the left femoral head 218 and tracked independently of each other by the surgical navigation system 20 throughout the procedure.A surgeon can then move the fragments 218 and 224 of the left femur to match the theoretically derived positions based on registration in the mirrored volume data sets 228, 230 of the right femur 214.

[0062] Since only the relative position of parts of an unaffected bone with respect to the corresponding parts of the affected bone is of interest, there is no need to calculate the absolute positions of the volume data sets 220, 222, 226, 228, and 230 relative to the rest of the patient's body using local reference systems. Rather, the volume data sets and their associated reference systems can be chosen arbitrarily. Therefore, time and computing resources are saved because there is no need to create a local reference system. Of course, the method is not limited to work performed on a femur as described here, but can be used, with minor modifications, for any anatomical structure that exists essentially in a mirror image on opposite sides of a central axis of the body, such as arms, ribs, feet, hands, hips, etc.

[0063] The present invention also considers the relationship of spatial data from a data set relating to an anatomical structure at a first time to another data set of the same anatomical structure at a different time, such as an anatomical reference system. An exemplary situation described in the Fig. 6A and Fig. 6B, is the ability to preoperatively define an anatomical reference system that is inaccessible during a surgical procedure due to the position and draping of the patient on an operating table. In this example, a preoperative volume data set of a forearm 250, including image data of the underlying bone(s), is acquired using the tracked ultrasound probe 32 and the surgical navigation system 20 at a time when the forearm is accessible. For example, a first volume data set 252 is acquired at one location on the forearm 250 and a second volume data set 254 is acquired at another location on the forearm 250 when both locations are accessible, as in Fig. 6A. The preoperative data set preferably includes regions of the forearm 250 that will be accessible after the relevant area has been prepared and masked, or that will otherwise be inaccessible. An anatomical reference frame or other spatial data, such as a global reference frame 256 of the camera assembly 26, is defined at a stage when the anatomy is accessible, and the arbitrary reference frames 258 and 260 are defined for the volume data sets 252 and 254, respectively. Each reference frame 258 and 260 is uniquely identifiable from the associated volume data set, such as by a known relationship to the image moment of inertia of the respective volume data sets 252 and 254, as previously set forth.Once defined, the anatomical reference frame or other global reference frame 256 is geometrically mapped to the arbitrary reference frames 258 and 260 for the preoperative data sets, and a vector 262 is defined that associates the arbitrary reference frames 258 and 260 and the respective volume data sets 252 and 254 in a unique spatial relationship. During a subsequent surgery, the portion of the forearm 250 corresponding to the volume data set 254 may not be accessible to the ultrasound probe 32, for example, due to occlusion, as shown in FIG. Fig. 6B, or for other reasons. In this case, a subsequent volume data set 252' is acquired with the aid of the ultrasound probe 32 and the surgical navigation system 20, with significant overlap with the volume data set 252, and the arbitrary reference frame 258 is re-established to relate the anatomical or global reference frame 256 to the subsequent volume data set 252'. The arbitrary reference frame 258 may be re-established in any sufficient manner, for example, by mapping the image moments of inertia of the volume data sets 252 and 252' in a substantially similar manner as described hereinbefore, by other volume mapping methods or surface mapping methods, etc. The computer system 24 once again calculates the position of the second volume data set 254 based on the vector 262 using appropriate program routines, even though the region of the forearm 250 is inaccessible.In this way, the surgical navigation system 20 is capable of recalculating the location of portions of the bones of the forearm 250 even though only a previously identified volume portion of the bones is visible, without requiring the previously identified volume portions to be visible or, as described above, the definition of local anatomical landmarks. The example presented here can similarly be applied to any anatomical feature that maintains a relatively stable structural geometry over time, such as each bone, and can be extended to apply to any number of volume data sets that can be spatially linked.

[0064] In another application, functional data about an anatomical structure are developed by collecting a plurality of volume datasets from the same anatomical structure in a plurality of different positions at correspondingly different times, without the need to identify a local anatomical reference system. An example of this application is presented in the Fig. 7A and Fig.7B, where functional movement parameters of a patient's hip 270 are determined. In this example, a first volume data set 272 is acquired from a portion 274 of the patient's femur and a first volume data set 276 is acquired from a portion 278 of the pelvis, both with the patient's leg in an extended position. A second volume data set 272' is acquired from substantially the same portion of the patient's femur 274 and a second volume data set 276' is acquired from substantially the same portion 278 of the patient's pelvis, both with the patient's leg in a bent position. Each volume data set 272, 276, 272', and 276' is assigned an arbitrary reference frame 280, 282, 284, and 286, respectively, which is correlated to a known position with respect to a uniquely identifiable property of the respective volume data set.Preferably, each arbitrary reference frame 280, 282, 284, and 286 is correlated with an image moment of inertia of each volume data set 272, 276, 272', and 276', although other identifiable unique properties of a particular volume data set may be used, as set forth herein. Further position data, including a vector 288 between the volume data sets 272 and 276 and a vector 288' between the volume data sets 272' and 276', are calculated based on the volume data sets relative to a global reference frame 290, such as a reference frame of the camera assembly 26. In some applications, a gravity vector G may be correlated with one or more of the arbitrary reference frames 280, 282, 284, and 286, as previously described.The reference frames of different volume data sets of the same volume, such as 272 and 272', are registered to each other based on a uniquely identifiable feature of the volume, as previously set forth herein. The method of acquiring volume data sets of the same portion of the femur and the same portion of the pelvis may be repeated in several additional different positions to determine a cone of motion of the hip under normal motion conditions. The volume data sets 272, 276, 272', and 276' are preferably acquired using one or more ultrasound probes 32 tracked by the camera assembly 26 of the surgical navigation system 20 as previously described. In one method and system, each of the volume data sets 272, 276, 272', and 276' is acquired using a single tracked ultrasound probe 32.In such a system, there is preferably no movement of the femur and pelvis while the volume data sets are acquired in each position. In an alternative method and system, multiple tracked ultrasound probes 32 are used simultaneously to continuously acquire simultaneous data sets of each anatomical structure while, for example, the patient's leg is moved into different positions. Functional motion parameters of the hip joint that are spatially related to different volume data sets, such as a range of motion cone and the gravity vector G, can then be calculated based on the different volume data sets without the need to create and / or determine local anatomical reference frames based on predefined anatomical features.Preferably, one or more of the computer systems 24 connected to the surgical navigation system 20 perform the required calculations and store all associated data in dedicated data storage devices in a manner known to those skilled in the art. The same or similar functional movement analyses can be performed in a similar manner on other body parts.

[0065] Other embodiments with different combinations of the individual features of each of the embodiments described above are expressly included herein, INDUSTRIAL APPLICABILITY

[0066] The methods and systems described herein can facilitate the transfer of data from one dataset to another dataset, where the data in the other dataset would otherwise be unavailable or not readily available. The methods and systems disclosed herein advantageously utilize arbitrarily defined unique reference systems in different datasets to easily register the datasets and relate the data from one to another without requiring the labeling and use of specific landmarks that can be compared and / or mapped across two or more datasets.Particular procedures that may benefit from the findings disclosed here include surgical interventions such as hip arthroplasty to perform functional assessments during surgery and trauma surgery to mirror data from an unaffected anatomical structure to an affected anatomical structure.

[0067] Numerous modifications of the present invention will be apparent to those skilled in the art in light of the foregoing description. Accordingly, this description is to be considered as illustrative only and is presented to enable those skilled in the art to make and use the invention and to teach the best mode contemplated for carrying it out. Exclusive rights to all modifications which come within the scope of the appended claims are reserved. All patents and patent applications cited herein are incorporated herein in their entirety.

Claims

[1] A computer-assisted method for registering data associated with a first data set in a second data set, the method comprising the steps of: Acquiring a first data set of an anatomical structure with an image processing device; developing additional data for the first data set, the additional data having a uniquely identifiable spatial relationship to the structure of the first data set, the additional data including a gravity vector; Creating a first arbitrary reference system for the first data set, wherein the first reference system is created without reference to a preselected landmark in the structure and the first reference system has a unique spatial relationship to the first data set; Acquiring a second data set of the anatomical structure using an image processing device; Creating a second arbitrary reference system for the second data set; Transforming the first reference system to the second reference system by assigning a unique spatial parameter of the first data set to the same unique spatial parameter of the second data set, and Registration of the additional data in the second data set. [2] The method of claim 1, wherein the step of establishing a first reference system comprises the steps of: Calculating an inherent property of the first data set, wherein the inherent property has a unique position and orientation relative to the anatomical structure that can be identified from each reference position, and Correlation of the inherent property with the first arbitrary reference system. [3] A computer-assisted method for registering data associated with a first data set in a second data set, the method comprising the steps of: Acquiring a first data set of an anatomical structure with an image processing device; Developing additional data for the initial dataset, where the additional data have a uniquely identifiable spatial relationship to the structure of the initial dataset; Creating a first arbitrary reference system for the first data set, wherein the first reference system is created without reference to a preselected landmark in the structure and the first reference system has a unique spatial relationship to the first data set; Acquiring a second data set of the anatomical structure using an image processing device; Creating a second arbitrary reference system for the second data set; Transforming the first reference system to the second reference system by assigning a unique spatial parameter of the first data set to the same unique spatial parameter of the second data set, and Registration of the additional data in the second data set, where the step of creating a first reference system comprises the following steps: Calculating an inherent property of the first data set, wherein the inherent property has a unique position and orientation relative to the anatomical structure that can be identified from each reference position, and Correlation of the inherent property with the first arbitrary reference system, where the inherent property of the first data set comprises an image moment of inertia of the first data set. [4] The method of claim 2 or 3, wherein the step of establishing a second arbitrary reference system comprises the steps of: Determination of the inherent property in the second data set and Correlation of the inherent property with the second arbitrary reference system. [5] The method of claim 4, wherein the step of transforming comprises the step of: Registering the first data set with the second data set based on the inherent property, wherein the registration step is performed by a computer. [6] The method of claim 5, further comprising the step of displaying the additional data in the registry with the second data set on a display device, and wherein the acquiring steps comprise acquiring data sets with a computer-assisted surgical navigation system. [7] A computer-assisted method for associating spatial data related to a first volume data set of an anatomical structure with a second volume data set of that anatomical structure, comprising the following steps: Acquiring a first volume data set of the anatomical structure using a computer-assisted surgical navigation system; Assigning a first arbitrary reference system to the first volume data set; Calculating an inherent property of the first volume data set, wherein the inherent property has a unique position and orientation with respect to the anatomical structure that can be determined from any reference position; Correlation of the inherent property with the first arbitrary reference system; Associating additional spatial data with the first volume data set, wherein the additional spatial data has a unique spatial relationship correlated with the first arbitrary reference system; Acquisition of a second volume dataset of the anatomical structure using a computer-assisted surgical navigation system; Assigning a second arbitrary reference system to the second volume data set; Determination of the inherent property in the second volume data set; Correlation of the inherent property with the second arbitrary reference system; Registering the first volume data set with the second volume data set based on the inherent property, wherein the registration step is performed by a computer; Correlating the additional spatial data with the second volume dataset when registering it, and Displaying the additional spatial data in the registration with the second volume data set on a display device, wherein the steps of calculating the inherent property comprise the step of calculating the image moment of inertia of both the first and second volume data sets. [8] The method of claim 7, wherein the first volume data set and the second volume data set are acquired with the same modality. [9] The method of claim 8, wherein the modality comprises an ultrasound probe tracked by the computer-assisted surgical navigation system. [10] A computer-assisted method for associating spatial data related to a first volume data set of an anatomical structure with a second volume data set of that anatomical structure, comprising the following steps: Acquiring a first volume data set of the anatomical structure using a computer-assisted surgical navigation system; Assigning a first arbitrary reference system to the first volume data set; Calculating an inherent property of the first volume data set, wherein the inherent property has a unique position and orientation with respect to the anatomical structure that can be determined from any reference position; Correlation of the inherent property with the first arbitrary reference system; Associating additional spatial data with the first volume data set, wherein the additional spatial data has a unique spatial relationship correlated with the first arbitrary reference system; Acquisition of a second volume dataset of the anatomical structure using a computer-assisted surgical navigation system; Assigning a second arbitrary reference system to the second volume data set; Determination of the inherent property in the second volume data set; Correlation of the inherent property with the second arbitrary reference system; Registering the first volume data set with the second volume data set based on the inherent property, wherein the registration step is performed by a computer; Correlating the additional spatial data with the second volume dataset when registering it, and Displaying the additional spatial data in the registration with the second volume data set on a display device, wherein the step of associating additional spatial data comprises the steps of identifying a gravity vector and correlating the gravity vector with the first arbitrary reference frame. [11] The method of claim 10, further comprising the step of displaying the gravity vector on the screen upon registration with the second volume data set. [12] The method of claim 7 or 10, wherein the step of associating additional spatial data comprises the following steps: Acquisition of a third volume dataset of a different anatomical structure; Assigning a third arbitrary reference system to the third volume data set; Calculating an inherent property of the third volume dataset, wherein the inherent property has a unique position and orientation with respect to the other anatomical structure that can be determined from any reference position; Correlating the inherent property of the third volume data set with the third arbitrary reference system, and Calculate a unique position and orientation of the third arbitrary reference frame with respect to the first arbitrary reference frame. [13] The method of claim 12, wherein the third volume data set is not contiguous with the first volume data set. [14] The method of claim 13, wherein the other anatomical structure has a constant position relative to the anatomical structure. [15] The method of claim 14, wherein said anatomical structure and the other anatomical structure are parts of a single bone. [16] The method of claim 14, wherein said anatomical structure is part of a first bone and the other anatomical structure is part of a second bone. [17] The method of claim 16, wherein the first bone is a femur and the second bone is a pelvis. [18] The method of claim 16, further comprising the step of calculating functional data of a joint between the first and second bones based on the additional spatial data. [19] The method of claim 12, wherein the first volume data set is acquired at a first time and the second volume data set is acquired at a second time. [20] The method of claim 19, wherein the first volume data set and the third volume data set are acquired while said anatomical structure and the other anatomical structure are in a first fixed general position. [21] The method of claim 20, wherein the second volume data set is acquired while the anatomical structures are in a second general position. [22] The method of claim 21, wherein the first and third volume data sets are acquired preoperatively and the second volume data set is acquired intraoperatively. [23] A system for acquiring and processing a volume data set of an anatomical structure, comprising: Means for acquiring a first volume data set of an anatomical structure of a patient and a second volume data set of the anatomical structure; means for calculating an inherent property of the first volume data set and the second volume data set, the inherent property having a unique position and orientation with respect to the anatomical structure that can be determined from each reference position; means for assigning a first arbitrary reference system to the first volume data set and a second arbitrary reference system to the second volume data set; means for correlating the inherent characteristic with the first arbitrary reference system; means for associating additional spatial data with the first volume data set, the additional spatial data having a unique spatial relationship correlated with the first arbitrary reference system; means for registering the first volume data set with the second volume data set based on the inherent property, and Means for correlating the additional spatial data with the second volume data set when registered therein, wherein the means for calculating comprise a computer-aided routine for calculating an image moment of inertia of the first and second volume data sets. [24] The system of claim 23, further comprising means for determining the orientation of the anatomical structure or portions thereof with respect to the gravitational vector in the first volume data set. [25] The system of claim 23, wherein the means for detecting comprises a computer-assisted surgical navigation system and an ultrasound probe. [26] A system for acquiring and processing a volume data set of an anatomical structure, comprising: Means for acquiring a first volume data set of an anatomical structure of a patient and a second volume data set of the anatomical structure; means for calculating an inherent property of the first volume data set and the second volume data set, the inherent property having a unique position and orientation with respect to the anatomical structure that can be determined from each reference position; means for assigning a first arbitrary reference system to the first volume data set and a second arbitrary reference system to the second volume data set; means for correlating the inherent characteristic with the first arbitrary reference system; means for associating additional spatial data with the first volume data set, the additional spatial data having a unique spatial relationship correlated with the first arbitrary reference system; Means for registering the first volume data set with the second volume data set based on the inherent property, Means for correlating the additional spatial data with the second volume data set when registered therein, wherein the means for assignment comprises means for identifying functional data with respect to the first volume data set, and wherein the means for identifying functional data comprises means for identifying a gravity vector. [27] The system of claim 26, wherein the means for identifying comprises means for identifying movement parameters of a joint. [28] The system of claim 23 or 26, wherein the means for associating comprises means for calculating a unique position and orientation of a third arbitrary reference system with respect to the first arbitrary reference system. [29] The system of claim 23 or 26, wherein the means for assigning comprises means for assigning the first and second reference systems without reference to a predefined landmark of the anatomical structure. [30] A method for establishing a position of a portion of a bone which has been altered from a normal shape, comprising the steps of: Acquiring a first volume data set for a first bone that is unaltered, the first volume data set comprising volume data of a first and second portion of the first bone; Identification of a first unique spatial feature of the volume data for the first part of the first bone; Creating a first arbitrary reference system for the first volume dataset correlated with the first unique spatial feature; Identification of a unique spatial relationship between the first arbitrary reference system and the second part of the first bone; Identifying a second bone that normally mirrors the first bone about a central axis, the second bone having a first part and a second part that substantially correspond as mirror structures to the first and second parts of the first bone, respectively, and the second bone having been altered from a normal shape such that the first part of the second bone is in an altered position relative to the second part of the second bone; Acquiring a second volume dataset of the first part of the second bone; identifying a second unique spatial feature of the second volume data set, wherein the second unique spatial feature substantially mirrors the first unique spatial feature; Registering the first volume data set with the second volume data set in mirrored correlation by correlating the first unique spatial feature with the second unique spatial feature, and Restoration of the normal position of the second part of the second bone so that it coincides with the position of the second part of the first bone with respect to the registered position of the first part of the first bone. [31] The method of claim 30, wherein the unique spatial relationship comprises a position vector between the volume data set for the first part of the first bone and the volume data set for the second part of the first bone. [32] The method of claim 30, wherein the first portion of the second bone is severed from the second portion of the second bone by trauma. [33] The method of claim 30, wherein the first and second volume data sets are acquired with an ultrasound probe tracked by a computer-assisted surgical navigation system. [34] The method of claim 33, further comprising tracking the positions of the first and second portions of the second bone with a tracking device tracked by the computer-assisted surgical navigation system. [35] The method of claim 30, wherein the first arbitrary reference system is created without reference to a predefined landmark of the anatomical structure. [36] The method of claim 30, wherein the steps of identifying the first and second unique spatial features comprise the step of calculating an image moment of inertia of the volume data sets.

Images