FIELD OF THE INVENTION

[0001 ] The present invention relates to systems and methods for visualisation of moving objects. In particular examples, there is disclosed a method and/or system for reducing the effects of deformation movement of an examined body. For example, this assists in dealing with patient bodily movements when a patient is undergoing a rotation whilst receiving a cone beam computed tomography scan.

BACKGROUND OF THE INVENTION

[0002] In a conventional cone beam computer tomography (CBCT) scan, projections at different angles are acquired by rotating a linear accelerator (linac) gantry around a patient. Alternatively, spatially distributed projections can also be acquired by rotating the patient while keeping the linac gantry static. The latter option is more economical as rotating the treatment couch is mechanically easier than rotating the heavy and sophisticated linac gantry. During patient rotation, the patient's organs are likely to move and deform in a way which is coupled to the rotation (and hence image acquisition) itself, making image reconstruction under patient rotation a challenging problem. These movements may be due to gravitation and other effects. The movements lead to incorrect and imprecise processing of captured imagery.

[0003] There is a need for new or improved systems for visualisation of moving objects and/or methods or processes for visualisation of moving objects. [0004] The reference in this specification to any prior publication (or information derived from the prior publication), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that the prior publication (or information derived from the prior publication) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates. SUMMARY OF THE INVENTION

[0005] The present invention aims to provide for improved imaging of objects undergoing variable relative transformation during scanning. [0006] In accordance with a first example aspect of the present invention, there is provided a method of reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body, the method including the steps of: (a) acquiring a series of projections around a patient wherein the projections can include the angular rotation of the examined body relative to a gravitational reference frame; (b) sorting the projections into a series of angularly correlated bins, for different angular rotations of the examined body; (c) constructing a deformation blurred image from the projections as an initial prior image; and (d) utilising the initial prior image and the projections for an angular bin to optimise a digital tomosynthesis reconstruction of the projections of at least one angular bin. [0007] In some embodiments, the step (d) preferably can include iteratively optimising the digital tomosynthesis reconstructions. Both the examined body and the projection acquisition equipment can undergo opposed angular rotations in the gravitational reference frame. In some embodiments, the series of angularly correlated bins are preferably adjacent one another. The angular size of the bins can be about 20 degrees. The optimisation of step (d) preferably can include the minimisation of the mismatch between a reconstructed solution and the acquired projection data. The optimisation of step (d) preferably can include the minimisation of the difference between the digital tomosynthesis reconstruction and the deformation blurred image. The optimisation of step (d) preferably can include the minimisation of intensity variations in the the digital tomosynthesis reconstruction. The optimisation of step (d) preferably can include the minimisation of changes in the deformation vector field between reconstructed volumes of adjacent angular bins. The optimisation of step (d) preferably can include the minimisation of spatial variations in the deformation vector field of the reconstructed volumes.

[0008] In a further example aspect, there is provided a method of reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body, the method including the steps of: (a) acquiring projections of the examined body, for a series of angular displacements, by angular rotation of the examined body; (b) sorting the projections into a series of angularly correlated bins, each bin corresponding to a range of angular displacements; (c) constructing a deformation -blurred 3D image from the projections as an initial prior image; and (d) producing, for each bin, a digital tomosynthesis reconstruction using the deformation-blurred 3D image and the projections of the respective bin.

[0009] In a further example aspect, there is provided a system for reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body, the system including: a scanning device configured to acquire projections of the examined body, for a series of angular displacements, by angular rotation of the examined body; a processing system configured to: sort the projections into a series of angularly correlated bins, each bin corresponding to a range of angular displacements; construct a deformation -blurred 3D image from the projections as an initial prior image; and produce, for each bin, a digital tomosynthesis reconstruction using the deformation-blurred 3D image and the projections of the respective bin.

BRIEF DESCRIPTION OF THE DRAWINGS

[001 0] Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:

[001 1 ] Fig. 1 illustrates schematically a tomographic scan under patient rotation and the concept of "angular bins".

[001 2] Fig. 2 illustrates a flowchart or workflow of the angular-correlated image reconstruction method.

[001 3] Fig. 3 illustrates some example comparisons with conventional CBCT and the method of the preferred embodiment. [0014] Fig. 4 illustrates a flowchart or workflow of an example method for reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body.

[001 5] Fig. 5 illustrates an example system for reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body. [001 6] Fig. 6 illustrates an example processing system for use in the system of Fig. 5.

[001 7] Fig. 7 illustrates further example comparisons with conventional CBCT and the method of the preferred embodiment.

DETAILED DESCRIPTION

[001 8] Example embodiments relate to systems and/or methods for visualisation of moving objects. In particular examples, there is disclosed a method and/or system for reducing the effects of deformation movement of an examined body. For example, this assists in dealing with patient bodily movements when a patient is undergoing a rotation whilst receiving a cone beam computed tomography scan. In example embodiments, there is provided a solution to obtaining more stable imagery from a rotated subject form of Linac Gantry analysis.

[001 9] Turning initially to Fig. 1, there is illustrated 1 schematically a tomographic scan under patient rotation and the concept of "angular bins" in the arrangement of the preferred embodiment. In this arrangement 1, a patient or subject 2 (e.g. a person or an animal) is placed on a support couch 3 (or another suitable support or retention device), and subjected to X-ray radiation from an X-ray source 4. The support couch is subject to a predetermined rotation 9, around a central axis, such that, at a later time t, it is in position 8. The patient also rotates 7 on the support couch. The resulting rotation causes various portions of the patient's anatomy to undergo relative movement.

[0020] In order to minimise the variations, in the preferred embodiment, projections are sorted into a series of different Angular Bins e.g. 10, 11, 12. Projections are two-dimensional images formed by X-ray radiation (or other types of waves, such as ultrasounds, radio waves, proton beams, depending on the imaging technique) incident on a detector plane (delimited by points 5 and 6 in Fig. 1).

[0021 ] The variation in gravitational deformation within each angular bin is assumed to have minimal effects on the reconstruction, and the method performs "angular-correlated" image reconstruction. The method can be applied to both horizontal rotation (patient in a lying position) and vertical rotation (patient in an upright position). The method is a data-driven technique and requires no pre-acquired information of the image other than the projection data.

[0022] The workflow of the method can be as set out 20 in Fig. 2. Assuming a full projection set is initially obtained 21, the following major steps are implemented:

[0023] 1. Sort the projections into angularly-correlated bins 22.

[0024] 2. Reconstruct the deformation-blurred volume and use it as a prior image 23. [0025] 3. Perform an iterative reconstruction of the digital-tomosynthesis of each angular bin 24.

[0026] The resulting output 26 of the method is multiple deformation-resolved 3D volumes of the subject. [0027] The embodiment will now be discussed in more detail. In the following, the volume to be reconstructed is denoted as , the full projection data set is denoted as P , and the Radon transform (i.e. the forward projection operator) is denoted as R.

[0028] Step 1: Sort the projections into angularly-correlated bins 22. [0029] The full projection set P is first sorted into **sn. angular bins, CP*' !¾· ^» ··-· , each bin covering a certain angular range of patient rotation. The angular bins can be next to each other, overlapping with each other or spaced apart from each other. This approach is based on the assumption that within each angular bin the variation in gravitational deformation leads to minimal deformation blur in the reconstruction of each individual bin. In a first example, a 20-degree bin width was used with adjacent bins next to each other, i.e. bin 1 ranges from -10 to 10 degrees, bin 2 ranges from 10 to 30 degrees, etc.

[0030] The reconstruction of each angular bin is similar to a digital-tomosynthesis (DTS) reconstruction. DTS refers to the use of a narrow angular range of projections (typically 10-90 degrees) to reconstruct a 3D volume in order to reduce imaging dose and time. Example DTS reconstruction methods are provided in Godfrey D, Yin F, Oldham M, Yoo S and Willett C 2006 Digital tomosynthesis with an on-board kilovoltage imaging device Int. J. Radiat. Oncol. Biol. Phys. 65(1), 8-15; Descovich M, Morin O, Aubry J F, Aubin M, Chen J, Bani-Hashemi A and Pouliot J 2008 Characteristics of megavoltage cone -beam digital tomosynthesis Med. Phys. 35(4), 1310-1316; and Maurer J, Godfrey D, Wang Z and Yin F F 2008 On-board four-dimensional digital tomosynthesis: First experimental results Med. Phys. 35(8), 3574-3583.

[0031 ] Unlike a tomographic reconstruction, a DTS reconstruction suffers from anisotropic spatial resolution. Spatial resolution is most degraded along the "in-depth" direction, i.e. the direction pointing from the rotation center of the patient to the middle angle of the angular bin. A smaller bin width leads to a worse in-depth resolution. There is therefore a trade-off between in- depth resolution and the amount of deformation in a bin. As a result, the optimal bin width may vary from case to case and depend on the imaging purpose. In the alternative, non-uniform bin widths can also be used.

[0032] Step 2: Reconstruct the deformation-blurred volume and use it as a prior image 23.

[0033] To compensate for the loss in the in-depth resolution, a prior image is first reconstructed by FDK backprojecting the entire unsorted projection set P , for example, using the method of Feldkamp L, Davis L and Kress J 1984 Practical cone-beam algorithm J. Opt. Soc. Am. A Opt. Image. Sci. Vis. 1(6), 612-619. The result is a 3D tomographic image with isotropic spatial resolution, which will be prone to blurring caused by gravitational deformation. The deformation- blurred image, ¾iajr?d , is later included in the DTS reconstruction of each angular bin. [0034] Step 3: Perform an iterative reconstruction of the digital -tomosynthesis of each angular bin 24.

[0035] The DTS reconstruction of each angular bin may be challenging as the sorted projection set in each bin is highly undersampled and contains only image information in certain views. To address these issues, the reconstruction can be classified as an optimization problem with a hybrid objective function, for ⁵¹ = i,2,3, <.., !¾ j _a . :

1

f _n = argmiii^ || f - p _n \ ^ + A[sT¥(f - fg _& ^ ) + (1 - ) (f§] ,

[0036] Such an objective minimization problem can be solved by the nonlinear conjugate gradient method in an iterative manner, for example, using the method of Chen G H, Tang J and Leng S 2008 Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets Med. Phys. 35(2), 660-663. The first term in the equation 1 represents the mismatch between the reconstructed solution and the acquired data. The remaining terms are additional total-variation based regularization terms used to assist the algorithm in finding a unique solution to the undersampled dataset Ps . The total-variation, denoted as is the 11 -norm of the image gradient. The Wlf— term imposes a similarity constraint on the solution, thereby incorporating the information in the in-depth direction in the deformation-blurred image into the reconstruction. The T¥(f } term regularizes intensity variations in the image, thereby reducing noise and artifacts. The ^& value controls the balance between the two regularization terms, and the ^ value controls the overall regularization strength. [0037] In scenarios where the minimisation of equation (1) is insufficient for a high quality reconstruction, the hybrid objective function to be minimised can include additional terms based on the deformation vector fields of the reconstructed volumes. One example would be to include the minimisation of the changes in the deformation vector fields between reconstructed volumes of adjacent angular bins. Another example would be to include minimisation of spatial variations of the deformation vector fields of the reconstructed volumes.

[0038] Referring to Fig. 4, there is provided another example method 400 of reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body. Method 400 allows for the generation of a 3D CBCT image of the examined body, or of a target within the examined body (e.g. a tumour), where the examined body is in motion during image-acquisition phase. The acquired images are two-dimensional images and may be X-ray scans, or projections.

[0039] Method 400 includes step 410 of acquiring projections of the examined body, for a series of angular displacements, by angular rotation of the examined body. In other examples, the examined body may undergo other types of motions, such as translational motion, or a combination of translational and rotational motion. Then, at step 420, sorting the projections into a series of angularly correlated bins, each bin corresponding to a range of angular displacements.

[0040] At step 430, constructing a deformation-blurred 3D image from the projections as an initial prior image. The initial prior image is known as a "deformation -blurred 3D image" because the projections from which it is constructed may illustrate the examined body, or target, in a physically deformed, or blurred, state. The deformed state of the examined body, or target, is due to deformations, or distortions, arising from its motion. For example, if the examined body is a soft- tissue body and it is rotated in a gravitational reference frame, it may be temporarily physically deformed. Therefore, a 3D image of the examined body constructed from various two-dimensional projections of the rotating examined body will be blurred, or made indistinct, or ill-defined. Centripetal force, inertia, or other forces may further contribute to deforming, or distorting, the examined body, and hence, its constructed 3D image.

[0041 ] Then, at step 440, producing, for each bin, a digital tomosynthesis (DTS) reconstruction using the deformation-blurred 3D image and the projections of the respective bin. Since step 440 is executed for each bin, the "respective bin" is the particular bin for which step 440 is being executed. The reconstruction may occur through the method described above for Fig. 2. Alternatively, other DTS reconstruction algorithms may be used.

[0042] In some examples, method 400 may further include step 450 of generating, using the digital tomosynthesis reconstruction for each bin, vectors describing changes in deformations of the examined body from the respective bin to a next bin. In some examples, a set of deformation vector fields, which describe how the scanned object deforms from one angular bin to another, can be obtained using a deformable image reconstruction method, such as that of Klein, S. et al. 2010 elastix: A Toolbox for Intensity -Based Medical Image Registration IEEE Transactions on Medical Imaging 29(1) 196-205. In some examples, a bin is attributed a vector field which characterises changes in the deformations of the examined body relative to an adjacent bin. Each bin may be attributed one such vector filed. Alternatively, a bin may be attributed multiple vector fields describing changes in the deformations of the examined body relative to multiple other bins.

[0043] Then, at step 460, producing, for each bin, a warped 3D image using the projections and the vectors. Using the deformation vector fields, a 3D image of the object at every angular bin can be reconstructed using the entire projection set, for example, by utilising a "warp-backprojection" approach, such as that of Rit, S. et al. 2009 On-the-fly motion-compensated cone -beam CT using an a priori model of the respiratory motion Medical Physics 36(6) 2283-2296. The warp- backprojection approach deforms a backprojected ray from each projection image using the deformation vector fields. This results in higher quality reconstructions for all angular bins with most of the deformation components resolved.

[0044] In some examples, method 400 may further include step 470 of repeating steps 450 and 460, wherein for subsequent iterations of step 460, the vectors are generated using the warped 3D images of previous iterations. The higher quality reconstructions (i.e. warped 3D images) resulting from step 460 can be used to improve the deformation vector fields resulting from step 450, for example, using a deformable image registration of Klein, S. et al. 2010 elastix: A Toolbox for Intensity-Based Medical Image Registration IEEE Transactions on Medical Imaging 29(1) 196— 205. The improved deformation vector fields can also be used to improve the warp-backprojection reconstructions. Therefore, steps 450 and 460 can be repeated, thereby iteratively improving both the reconstructed images and the deformation vector fields. The iterations may be stopped when the changes in the reconstructed images between iterations fall below a certain threshold.

[0045] Although the steps of method 400 may be executed sequentially, certain steps may be executed simultaneously, or in any order, for the purpose of accelerating the execution of method 400. For example, steps 420 and 430 may be executed sequentially, or in any order (i.e. step 430 prior to step 420, or step 420 prior to step 430). [0046] Referring to Fig. 5, there is illustrated an example system 500 for reducing the effects of deformation movement of an examined body in the computing of a 3D cone beam CT image of the examined body. System 500 includes a scanning device 510 configured to acquire projections of the examined body, for a series of angular displacements, by angular rotation of the examined body. System 500 further includes a processing system 520. Processing system 520 is configured to sort the projections into a series of angularly correlated bins, each bin corresponding to a range of angular displacements. Processing system 520 further constructs a deformation-blurred 3D image from the projections as an initial prior image and produces, for each bin, a digital tomosynthesis reconstruction using the deformation-blurred 3D image and the projections of the respective bin.

[0047] Scanning device 510 may be an X-ray imaging device, or a kV imaging device, including an X-ray source and an X-ray detector. In some examples, scanning device 510 is a CT scanner or a diagnostic imaging device. In some examples, scanning device 510 is any device able to acquire a two-dimensional, or projected, image of the examined body, or of a target located within the examined body. In some examples, scanning device 510 is stationary (i.e. it does not rotate around the examined body). In other examples, scanning device 510 is further configured to rotate around the examined body. To this end, system 500 may further include a gantry or tracks to allow scanning device 510 to rotate. [0048] System 500 may further include a support structure for the examined body. The support structure may be a table, couch, chair, or platform able to support the examined body. The examined body may be a living organism, such as a human body or an animal body, or any other type of object such as a biological organ or a biological tissue. The support structure may include straps or harnesses for securing the examined body. The support structure may be configured to selectively rotate relative to an axis, which may be a horizontal or a vertical imaginary axis. The support structure may further be configured for other types of movement, such as translational motion. The support structure may be configured to rotate with either a uniform or non-uniform velocity. In some examples, a non-uniform velocity of rotation may be advantageous where a higher number of projections of the examined body are desirable at a particular angle or orientation.

[0049] In some examples, scanning device 510 is configured to rotate around the examined body in one direction (e.g. clockwise) while the examined body, or the support structure, rotates in an opposite direction (e.g. counter-clockwise). This may be advantageous since the relative motion between scanning device 510 and the examined body reduces the time required for a complete scanning cycle, and may thus reduce a patient's exposure to radiation.

[0050] Scanning device 510 may be in communication with processing system 520. Communication between scanning device 510 and processing system 520 may occur either through a wired or wireless connection. Each of scanning device 510 and processing system 520 may include further apparatus necessary for communication (e.g. transmitter and receiver). Preferably, though not necessarily, system 500 further includes a communication link 515 between scanning device 510 and processing system 520. Communication link 515 may be wired or wireless. Processing system 520 may be located within scanning device 510, or in proximity of scanning device 510, or remotely of scanning device 510. Communication link 515 allows transmission of the scanned image from scanning device 510 to processing system 520. Communication link 515 may further allow for transmission of any other data between scanning device 510 and processing system 520 (e.g. data from a surrogate signal). [0051 ] In some examples, processing system 520 is further configured to generate, using the digital tomosynthesis reconstruction for each bin, vectors describing changes in deformations of the examined body from the respective bin to a next bin and to produce, for each bin, a warped 3D image using the projections and the vectors.

[0052] In some examples, processing system 520 further includes a graphics processing unit (GPU) or a visual processing unit (VPU). The GPU may be used to accelerate certain functions, such as the construction of a deformation-blurred 3D image, or the tomosynthesis reconstructions, or the production of warped 3D images.

[0053] Referring to Figure 6, there is illustrated an example processing system 520. In particular, the processing system 520 generally includes at least one processor 602, or processing unit or plurality of processors, memory 604, at least one input device 606 and at least one output device 608, coupled together via a bus or group of buses 610. In certain embodiments, input device 606 and output device 608 could be the same device. An interface 612 can also be provided for coupling the processing system 520 to one or more peripheral devices, for example interface 612 could be a PCI card or PC card. At least one storage device 614 which houses at least one database 616 can also be provided. The memory 604 can be any form of memory device, for example, volatile or non-volatile memory, solid state storage devices, magnetic devices, etc. The processor 602 could include more than one distinct processing device, for example to handle different functions within the processing system 600.

[0054] Input device 606 receives input data 618 and can include, for example, a data receiver or antenna such as a modem or wireless data adaptor, data acquisition card, etc. Input data 618 could come from different sources, for example scanning device 510 and/or with data received via a network. Output device 608 produces or generates output data 620, for example representing tomosynthesis reconstructions or warped 3D images, and can include, for example, a display device or monitor in which case output data 620 is visual, a printer in which case output data 620 is printed, a port for example a USB port, a peripheral component adaptor, a data transmitter or antenna such as a modem or wireless network adaptor, etc. Output data 620 could be distinct and derived from different output devices, for example a visual display on a monitor in conjunction with data transmitted to a network. A user could view data output, or an interpretation of the data output, on, for example, a monitor or using a printer. The storage device 614 can be any form of data or information storage means, for example, volatile or non-volatile memory, solid state storage devices, magnetic devices, etc. [0055] In use, the processing system 520 is adapted to allow data or information to be stored in and/or retrieved from, via wired or wireless communication means, the at least one database 616. The interface 612 may allow wired and/or wireless communication between the processing unit 602 and peripheral components that may serve a specialised purpose. The processor 602 receives instructions as input data 618 via input device 606 and can display processed results or other output to a user by utilising output device 608. More than one input device 606 and/or output device 608 can be provided. It should be appreciated that the processing system 520 may be any form of terminal, server, specialised hardware, or the like.

[0056] In some examples, system 500 is configured to implement method 400. Validation [0057] To validate the method, X-ray images of a porcine heart in the "lying position" were acquired. This experimental setup represents the more challenging embodiment of horizontal rotation of the method. A porcine heart was chosen as it is anatomically similar to the human heart. The porcine heart was placed in a polyvinyl chloride container and was surrounded with a few layers of bubble wrap. This setup imitates the presence of multiple organs surrounding the heart in a human body while still allowing for deformation. The container was secured and mounted onto a rotation platform that is able to rotate to an arbitrary angle as well as rotate at a constant speed specified by the user.

[0058] A conventional CBCT scan with the porcine heart fixed at zero-degree orientation was first acquired as a ground truth image for comparisons. The CBCT scan was reconstructed using FDK backprojection. Then, another scan was acquired with a static gantry and with the platform rotating at a constant speed of 3 degrees per second. The static gantry scan was reconstructed into 18 angular bins with a bin width of 20 degrees using the method. In both the conventional CBCT and static gantry acquisitions, 660 projections were acquired.

Results

[0059] Fig. 3 illustrates the images of the porcine heart acquired with conventional CBCT 31 and static gantry acquisitions 32. For the conventional CBCT case 31, different angular views of one single reconstructed volume with the porcine heart fixed at 0 degree are shown. For the static gantry case 32, a separate reconstruction from each angular bin is shown. The conventional CBCT image can be considered the ground truth for the 0 degree angular bin of the static gantry reconstruction. For all other angular bins, gravitational deformation is expected to be a main contributing factor of the differences between the conventional CBCT image and the static gantry images. (CAV=-250/1500 HU).

[0060] Deformation between the conventional CBCT case and the static gantry case was quantified by a magnitude of the deformation vector field (DVF) between the two images calculated via B -spline transformation-based deformable image registration (DIR). The 0-degree static gantry image was found to coincide with the conventional CBCT image, with a mean magnitude of <3 mm and maximum magnitude of <5 mm of the DVF. This indicates the accuracy of the reconstruction method for the static gantry scan, as the latter can be considered the ground truth of the former. Similar accuracies can be inferred for the other angular bins despite the absence of ground truth comparisons, since the reconstruction algorithm does not bias towards the 0-degree orientation. The mean deformation magnitude ranged from 3.0-8.9 mm, with up to 16.1 mm maximum deformation. Deformation was mainly observed in the downwards direction due to gravity.

[0061 ] The foregoing provides a data-driven method for reconstructing 3D volumes of continuously repositioned objects and was validated on a scan of a rotating porcine heart. The method represents a solution to imaging patients using a static gantry and a rotating couch.

[0062] Figure 7 illustrates further example comparisons with conventional CBCT and the method of the preferred embodiment. An imaging experiment involving a live white New Zealand rabbit was conducted on a portable C-arm imaging system (with ethics approval). The rabbit was anesthetized and secured in a rotation container. A sequence of 2D X-ray images with the rabbit continuously rotating at 6 deg/sec and the C-arm gantry at a fixed position was acquired. The method 400 was applied to the sequence of X-ray images to reconstruct the cone-beam CT volume of the rabbit at 0, 90, 180, and 270 degree container rotation. The set threshold for algorithm stopping criterion was a mean change in image pixel value of less than 0.001 mm ^"1 .

[0063] In addition to this, conventional cone -beam CT scans were acquired with the gantry rotating and the rabbit fixed at 0, 90, 180, and 270 degree container rotation. These cone-beam CT scans were used as reference images, which were compared to reconstruction results obtained using method 400. However, in the experiment, the reference cone-beam CT volumes could not be accurately reconstructed due to a lack of exact geometric information of the portable C-arm imaging system. Therefore, these reference images do not serve as the "ground truths", but are instead used for qualitative evaluation. [0064] Referring to Fig. 7, there is illustrated an uncorrected reconstruction (i.e. a deformation- blurred reconstruction) 710. Also illustrated are cone-beam CT reconstructions using method 400, and cone-beam CT reconstructions 730 using a conventional scanning method where the examined body remains stationary while a scanning device is rotated. Reconstruction 710 presents a large amount of blur due to gravitational deformations as one would expect. In contrast, the volumes 720 reconstructed using method 400 show almost no visually noticeable blur. The lungs and bony anatomy can be clearly identified.

[0065] The reconstructed volumes 720 also show some deformation between angles. In particular, the 90 degree and 270 degree reconstructions clearly deform towards the left and right near the bottom of the images. This deformation trend can also be observed in the reference cone- beam CT images 730.

[0066] These results indicate that the method was able to remove gravity-induced deformation blur, and to correctly recover the trend of deformation at each couch rotation angle. These findings indicate that the method is effective for reconstructing medical images acquired from a fixed- gantry geometry or, more generally, in any configuration where the examined body is in motion. Applications and Extensions

[0067] One envisioned application of the method of the embodiments is for imaging patients during radiation therapy procedures, in which a rotating patient presents a more cost-effective application than a rotating gantry in photon and charged particle therapy. The method can be used in a continuous manner such that as each new image is acquired a new volumetric image is created. The method can be used during radiation therapy beam delivery, where either the scatter from the radiation beam is accounted for or the imaging and radiation beams are alternately paused. The method can also be useful for a rotating gantry in which the patient position shifts during treatment and therefore the use of the angular bin represents a better image of the current anatomy than the full cone beam CT. [0068] A further extension of this method is to apply it to situations where both the gantry and the patient are rotating. The separation of images into physiological bins, for example respiratory and/or cardiac phases, to create so called 'four dimensional or 4D' or 'five dimensional or 5D' images is a well-known technique. The integration of the physiologic bins with the current method is a straightforward extension to the method. [0069] The current solution approach is one embodiment of solving the problem. Elements of the solution could be changed or included to solve the general problem.

Interpretation

[0070] Reference throughout this specification to "one embodiment", "some embodiments" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases "in one embodiment", "in some embodiments" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments.

[0071 ] As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner. [0072] In the claims below and the description herein, any one of the terms comprising, comprised of or which comprises is an open term that means including at least the elements/features that follow, but not excluding others. Thus, the term comprising, when used in the claims, should not be interpreted as being limitative to the means or elements or steps listed thereafter. For example, the scope of the expression a device comprising A and B should not be limited to devices consisting only of elements A and B. Any one of the terms including or which includes or that includes as used herein is also an open term that also means including at least the elements/features that follow the term, but not excluding others. Thus, including is synonymous with and means comprising.

[0073] As used herein, the term "exemplary" is used in the sense of providing examples, as opposed to indicating quality. That is, an "exemplary embodiment" is an embodiment provided as an example, as opposed to necessarily being an embodiment of exemplary quality.

[0074] It should be appreciated that in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, FIG., or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the Detailed Description are hereby expressly incorporated into this Detailed Description, with each claim standing on its own as a separate embodiment of this invention. [0075] Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those skilled in the art. For example, in the following claims, any of the claimed embodiments can be used in any combination. [0076] Furthermore, some of the embodiments are described herein as a method or combination of elements of a method that can be implemented by a processor of a computer system or by other means of carrying out the function. Thus, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element described herein of an apparatus embodiment is an example of a means for carrying out the function performed by the element for the purpose of carrying out the invention.

[0077] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description. [0078] Similarly, it is to be noticed that the term coupled, when used in the claims, should not be interpreted as being limited to direct connections only. The terms "coupled" and "connected," along with their derivatives, may be used. It should be understood that these terms are not intended as synonyms for each other. Thus, the scope of the expression a device A coupled to a device B should not be limited to devices or systems wherein an output of device A is directly connected to an input of device B. It means that there exists a path between an output of A and an input of B which may be a path including other devices or means. "Coupled" may mean that two or more elements are either in direct physical or electrical contact, or that two or more elements are not in direct contact with each other but yet still co-operate or interact with each other.

[0079] Thus, while there has been described what are believed to be the preferred embodiments of the invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such changes and modifications as falling within the scope of the invention. For example, any formulas given above are merely representative of procedures that may be used. Functionality may be added or deleted from the block diagrams and operations may be interchanged among functional blocks. Steps may be added or deleted to methods described within the scope of the present invention.