PROVISION OF A THERAPY PLAN

Abstract

A method for providing a therapy plan includes receiving a dataset. The dataset maps an examination object including a first tissue area at at least one first timepoint. The first tissue area is identified in the dataset as a first state. A second state is specified for the first tissue area. A therapy plan for a therapy apparatus is determined by application of a model to input data. A change in the first tissue area between the at least one first timepoint and at least one second timepoint is createable by the control of the therapy apparatus in accordance with the therapy plan. The model maps the first state to the second state and/or the second state to the first state. The therapy plan is provided as output data of the model.

Claims

1. A method for provision of a therapy plan, the method comprising: receiving a dataset that is preacquired, wherein the dataset maps an examination object including a first tissue area at at least one first timepoint; identifying a mapping of the first tissue area in the dataset as a first state; specifying a second state for the first tissue area, wherein the second state defines a spatial extent, a second tissue parameter of at least a part of the first tissue area at at least one second timepoint, or a combination thereof, the at least one second timepoint being after the at least one first point in time; determining a therapy plan for a therapy apparatus by application of a model to input data, wherein the input data is based on the dataset and the second state, wherein the therapy plan has at least one parameter for control of the therapy apparatus, wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan, wherein the model simulates a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof; and providing the therapy plan as output data of the model.

2. The method of claim 1, wherein the spatial extent is a maximum spatial extent.

3. The method of claim 1, wherein the dataset has at least one first tissue parameter of the first tissue area, a further tissue area, or the first tissue area and the further tissue area, wherein the further tissue area borders on the first tissue area.

4. The method of claim 3, wherein the model further simulates a mechanical interaction between the first tissue area and the further tissue area.

5. The method of claim 1, wherein identifying the mapping of the first tissue area comprises identifying a mapping of at least one critical structure, an edge area, or the at least one critical structure and the edge area of the first tissue area in the dataset, and wherein the model leaves out the at least one critical structure, the edge area, or the at least one critical structure and the edge area in the simulation of the change in the first tissue area.

6. The method of claim 1, wherein the second state defines a value, a range of values, or the value and the range of values for the spatial extent, the second tissue parameter of the at least one part of the first tissue area for the at least one second timepoint, a period of time comprising a number of second timepoints, up to a temporal maximum value, or comprising the number of second timepoints and up to a temporal maximum value, or any combination thereof.

7. The method of claim 6, wherein the first tissue area, in at least one area, borders on a further tissue area, and wherein the second state defines the value, the range of values, or the value and the range of values for the spatial extent, the second tissue parameter at least for the border, or a combination thereof.

8. The method of claim 1, wherein, during the control of the therapy apparatus in accordance with the therapy plan, at least one lesion is creatable in the first tissue area, wherein the model simulates a reduction in the spatial extent of the first tissue area, a change in the second tissue parameter as the change between the at least one first timepoint and the at least one second timepoint, or a combination thereof, and wherein the simulation of the change comprises a simulation of a transporting away of lysed tissue from the at least one lesion.

9. The method of claim 8, wherein the transporting is physiological transporting.

10. The method of claim 8, wherein the therapy apparatus has an ultrasound unit, wherein therapeutic ultrasound is emittable by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan into the first tissue area, wherein the at least one parameter predetermines a frequency, a bandwidth, an amplitude, a phase, a pulse duration, a focus position, a beam alignment, a beam shaping, a duty cycle, or any combination thereof of the therapeutic ultrasound, such that the at least one lesion is creatable in the first tissue area by the therapeutic ultrasound.

11. The method of claim 1, wherein determining the therapy plan comprises: determining a first simulated state of the first tissue area for the at least one first timepoint, the determining of the first simulated state comprising inverse simulating the biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, starting from a second initial state; adjusting the first simulated state to the first state, the adjusting of the first simulated state comprising adjusting the at least one parameter of the therapy plan and providing the adjusted first simulated state as the first initial state; determining a second simulated state of the first tissue area for the at least one second timepoint, the determining of the second simulated state comprising simulating the biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, starting from the first initial state; adjusting the second simulated state to the second state, the adjusting of the second simulated state comprising adjusting the at least one parameter of the therapy plan and providing the adjusted second simulated state as the second initial state, wherein the determining of the first simulated state, the adjusting of the first simulated state, the determining of the second simulated state, and the adjusting of the second simulated state are carried out repeatedly up to occurrence of an abort condition, and wherein, when the method is carried out for the first time: the method starts with the determining of the first simulated state and the second state is predetermined as the second initial state, or the method starts with the determining of the second simulated state, and the first state is predetermined as the first initial state; and a start value is received for the at least one parameter of the therapy plan, the start value is geometrically predetermined, or the start value is initialized by a random seed generator.

12. The method of claim 1, wherein the model comprises a trained function, wherein the method further comprises adjusting at least one parameter of the trained function by a comparison of a training therapy plan with a comparison therapy plan.

13. The method of claim 1, wherein the dataset maps an initial change in the first tissue area, wherein the initial change has been created before a beginning of the method by the therapy apparatus in accordance with an initial therapy plan, and wherein the dataset also has the initial therapy plan.

14. The method of claim 1, wherein providing the therapy plan comprises transmitting the at least one parameter to the therapy apparatus, performing a preparatory adjustment of at least one operating parameter, at least one positioning parameter, or the at least one operating parameter and the at least one positioning parameter to the therapy apparatus in accordance with the therapy plan, or a combination thereof.

15. The method of claim 14, wherein the transmitting, the performing, or the transmitting and the performing are without the control of the therapy apparatus.

16. A computer-implemented method for provision of a trained function, the computer-implemented method comprising: receiving a first training dataset that is preacquired, wherein the first training dataset maps an examination object including a first tissue area at at least one first timepoint; identifying a mapping of the first tissue area in the first training dataset; receiving a second training dataset that is preacquired, wherein the second training dataset maps the examination object including the first tissue area at at least one second timepoint after the first timepoint; identifying a further mapping of the first tissue area in the second training dataset as the second training state; receiving a comparison therapy plan for a therapy apparatus, wherein the comparison therapy plan has at least one parameter for control of the therapy apparatus, wherein, before the beginning of the computer-implemented method, between the at least one first timepoint and the at least one second timepoint, a change in the first tissue area has been created by the therapy apparatus in accordance with the comparison therapy plan; determining a training therapy plan for the therapy apparatus, the determining of the training therapy plan comprising applying the trained function to input data, wherein the input data is based on the first training dataset and the second training state, wherein the training therapy plan is provided as output data of the trained function; adjusting at least one parameter of the trained function, the adjusting of the at least one parameter of the trained function comprising comparing the training therapy plan with the comparison therapy plan; and providing the trained function.

17. A provision unit for provision of a therapy plan, the provision unit comprising: a processor configured to: receive a dataset that is preacquired, wherein the dataset maps an examination object including a first tissue area at at least one first timepoint; identify a mapping of the first tissue area in the dataset as a first state; specify a second state for the first tissue area, wherein the second state defines a spatial extent, a second tissue parameter of at least a part of the first tissue area at at least one second timepoint, or a combination thereof, the at least one second timepoint being after the at least one first point in time; determine a therapy plan for a therapy apparatus by application of a model to input data, wherein the input data is based on the dataset and the second state, wherein the therapy plan has at least one parameter for control of the therapy apparatus, wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan, wherein the model simulates a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof; and provide the therapy plan as output data of the model.

18. A system comprising: a provision unit for provision of a therapy plan, the provision unit comprising: a processor configured to: receive a dataset that is preacquired, wherein the dataset maps an examination object including a first tissue area at at least one first timepoint; identify a mapping of the first tissue area in the dataset as a first state; specify a second state for the first tissue area, wherein the second state defines a spatial extent, a second tissue parameter of at least a part of the first tissue area at at least one second timepoint, or a combination thereof, the at least one second timepoint being after the at least one first point in time; determine a therapy plan for a therapy apparatus by application of a model to input data, wherein the input data is based on the dataset and the second state, wherein the therapy plan has at least one parameter for control of the therapy apparatus, wherein a change in the first tissue area between the at least one first timepoint and the at least one second timepoint is createable through the control of the therapy apparatus in accordance with the therapy plan, wherein the model simulates a biological growth and the change in the first tissue area between the at least one first timepoint and the at least one second timepoint, and wherein the model maps the first state to the second state, the second state to the first state, or a combination thereof; and provide the therapy plan as output data of the model; and a therapy apparatus, wherein the therapy apparatus is configured to create the change in the first tissue area, wherein the provision unit is configured to control the therapy apparatus with the aid of the therapy plan such that the change is created in the first tissue area between the at least one first point in time and the at least one second point in time.

19. The system of claim 18, wherein the therapy apparatus includes an ultrasound unit, wherein the ultrasound unit is configured to send therapeutic ultrasound into the first tissue area, and wherein the therapeutic ultrasound is configured to create at least one lesion in the first tissue area as the change.

20. The system of claim 18, further comprising a medical imaging device, wherein the medical imaging device is configured to record, provide, or record and provide the dataset.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0136] Exemplary embodiments of the invention are shown in the drawings and will be described in greater detail below. In different figures, the same reference characters are used for the same features. In the drawings:

[0137] FIG. 1 shows a schematic diagram of an embodiment of a method for provision of a therapy plan;

[0138] FIG. 2 shows a schematic diagram of one embodiment of an inverse simulation of biological growth and a change in a first tissue area,

[0139] FIGS. 3 to 5 show schematic diagrams of further embodiment of the method for provision of a therapy plan;

[0140] FIG. 6 shows a schematic diagram of an embodiment of a method for provision of a trained function;

[0141] FIG. 7 shows a schematic diagram of one embodiment of a system;

[0142] FIG. 8 shows a schematic diagram of one embodiment of a provision unit; and

[0143] FIG. 9 shows a schematic diagram of one embodiment of a proposed training unit.

DETAILED DESCRIPTION

[0144] Shown schematically in FIG. 1 is an embodiment of a method (e.g., a computer-implemented method) for provision PROV-TP of a therapy plan TP. In a first act, a preacquired dataset DS may be received REC-DS. In this case, the dataset DS may map an examination object including a first tissue area TA1 at at least one first point in time. Further, in a second act, a mapping of the first tissue area TA1 may be identified ID-TA1 in the dataset DS as a first state. In a third act, a second state S2 may be specified DET-S2 for the first tissue area TA1. In this case, the second state S2 may define a spatial extent (e.g., a maximum) and/or a second tissue parameter of at least a part of the first tissue area TA1 at at least one second point in time after the at least one first point in time. In a fourth act, a therapy plan TP for a therapy apparatus may be determined by application of a model to input data DET-TP. In this case, the input data may be based on the dataset DS and the second state S2. The therapy plan TP may further have at least one parameter for control of the therapy apparatus. Further, a change in the first tissue area TA1 between the at least one first point in time and the at least one second point in time may be able to be created through the control of the therapy apparatus in accordance with the therapy plan. The model may further simulate a biological growth SIM-G and the change SIM-CH in the first tissue area between the at least one first point in time and the at least one second point in time. In this case, the model may map the first state to the second state S2 or the second state S2 to the first state. In a fifth act, the therapy plan TP may be provided PROV-TP as output data of the model.

[0145] In one embodiment, the identification ID-TA1 of the mapping of the first tissue area TA1 may include an identification of a mapping of at least one critical structure and/or of an edge area of the first tissue area TA1 in the dataset DS. In this case, the model may leave out the at least one critical structure and/or the edge area in the simulation of the change in the first tissue area TA1.

[0146] The second state S2 may further define a value and/or a range of values for the spatial extent and/or the second tissue parameter of the at least one part of the first tissue area TA1 for the at least one second point in time and/or a period of time including a number of second points in time and/or up to a temporal maximum value.

[0147] The dataset DS may further map an initial change in the first tissue area TA1 (e.g., on a time-resolved basis) at a number of first points in time. In this case, the initial change in the first tissue area TA1 may have been created before the beginning of the method by the therapy apparatus in accordance with an initial therapy plan. The dataset may additionally have the initial therapy plan.

[0148] In one embodiment, the provision PROV-TP of the therapy plan TP may include a transmission of the at least one parameter to the therapy apparatus and/or a preparatory adjustment of at least one operating parameter and/or at least one positioning parameter to the therapy apparatus in accordance with the therapy plan TP (e.g., without the control of the therapy apparatus).

[0149] Shown schematically in FIG. 2 is a form of embodiment of a simulation (e.g., an inverse simulation) of the biological growth SIM-G and the change SIM-G in the first tissue area TA1. The model may determine the therapy plan TP through inverse simulation (e.g., temporal backward simulation) of the biological growth SIM-G and the change SIM-CH in the first tissue area TA starting from the second state S2 between the at least one first point in time and the at least one second point in time. In this case, the model may map the second state S2 to the first state. As an alternative or in addition, the model may determine the therapy plan TP through simulation (e.g., temporal forwards simulation) of the biological growth SIM-G and the change SIM-CH of the first tissue area TA starting from the first state between the at least one first point in time and the at least one second point in time. In this case, the model may map the first state to the second state S2.

[0150] Described below by way of example is the inverse simulation of the biological growth SIM-G and the change SIM-CH in the first tissue area TA starting from the second state S2. The first tissue area TA1 may border on a further tissue area TA2 in at least one area. The dataset may further have a mapping of the first tissue area TA1 and of the further tissue area TA2. Further, the second state S2 may define the value (e.g., the maximum value) and/or the range of values for the spatial extent of the first tissue area and/or the second tissue parameter at least for the border. For example, the maximum value for the spatial extent of the at least one part of the first tissue area TA1 may be predetermined directly or indirectly (e.g., as minimum value S2′ of a spatial extent of the further tissue area TA). Account may also be taken here of an interstitial area between the first tissue area TA1 and the further tissue area TA2.

[0151] The inverse simulation of the biological growth SIM-G of the first tissue area TA1 may include a simulated shrinkage of the first tissue area TA (e.g., of volume elements uninfluenced by the therapy apparatus) starting from the second state S2, between the at least one first point in time and the at least one second point in time. In FIG. 2, the result of the inverse simulation of the biological growth SIM-G (e.g., the result of the simulated shrinkage) of the first tissue area TA1 is illustrated by the simulated state S2.G.

[0152] The control of the therapy apparatus in accordance with the therapy plan TP enables at least one lesion S2.L to be able to be created in the first tissue area TA1. In this case, the model may simulate SIM-CH a reduction of the spatial extent of the first tissue area TA1 and/or a change in the second tissue parameter as the change between the at least one first point in time and the at least one second point in time. For this, the inverse simulation of the change SIM-CH of the first tissue area TA1 may include an occurrence (e.g., an appending) of volume elements S2.CH uninfluenced by the therapy apparatus in the first tissue area TA1 starting from the second state S2 or starting from the result S2.G of the inverse simulation of the biological growth SIM-G. Further, the inverse simulation of the change SIM-CH may include an inverse simulation of a, for example, physiological transporting away from lysed tissue from the at least one lesion S2.L. The at least one lesion S2.L may arise as a result of the inverse simulation of the change SIM-CH of the first tissue area TA1 from the volume elements influenced by the therapy apparatus S2.CH.

[0153] The therapy apparatus may further have an ultrasound unit. In this case, the therapeutic ultrasound may be able to be emitted into the first tissue area TA1 by the ultrasound unit during the control of the therapy apparatus in accordance with the therapy plan TP. The at least one parameter may further predetermine a frequency, a bandwidth, an amplitude, a phase, a pulse duration, a focus position, a beam alignment, a beam shaping, and/or a duty cycle of the therapeutic ultrasound such that the at least one lesion S2.L in the first tissue area TA.1 is able to be created by the therapeutic ultrasound.

[0154] FIG. 3 shows a schematic diagram of a further embodiment of the method for provision PROV-TP of a therapy plan TP. In this embodiment, the dataset DS may have at least one first tissue parameter PARAM1 of the first tissue area TA1 and/or of a further tissue area TA2, with the further tissue area TA2 bordering on the first tissue area TA1. In one embodiment, the model may further simulate a mechanical interaction between the first tissue area TA1 and the further tissue area TA2 SIM-WW.

[0155] Shown schematically in FIG. 4 is a further embodiment of the method for provision PROV-TP of therapy plan TP. In this embodiment, the determination DET-TP of the therapy plan TP may include the acts a.1) to b.1). The method may start when first executed with the act a.1), for example, where the second state is predetermined as the second initial state. Further, a start value for the at least one parameter of the therapy plan TP may be received, geometrically predetermined, or initialized by a random seed generator INIT-TP. In act a.1), a first simulated state S1-SIM of the first tissue area TA1 may be determined for the at least one first point in time by inverse simulation of the biological growth SIM-G and of the change SIM-CH of the first tissue area TA1 between the at least one first point in time and the at least one second point in time, starting from the second initial state. In a further act a.2), the first simulated state S1-SIM may be adjusted ADJ-S1-SIM to the first state by adjustment ADJ-TP of the at least one parameter of the therapy plan TP. Further, the adjusted first simulated state S1-SIM-ADJ may be provided as the first initial state. Further, in a further act b.1), a second simulated state S2-SIM of the first tissue area TA1 may be determined for the at least one second point in time by simulation of the biological growth SIM-G and the change SIM-CH of the first tissue area TA1 between the at least one first point in time and the at least one second point in time, starting from the first initial state. In a further act b.2), the second simulated state S2-SIM may be adjusted ADJ-S2-SIM to the second state S2 by adjustment ADJ-TP of the at least one parameter of the therapy plan TP. Further, the adjusted second simulated state S2-SIM-ADJ may be provided as the second initial state. In one embodiment, the acts a.1) to b.2) may be carried out repeatedly Y until an abort condition E. In FIG. 4, the temporal direction (e.g., the inversion) of the simulation of the biological growth SIM-G and of the change SIM-CH of the first tissue area TA1 are illustrated by arrows pointing in different directions.

[0156] FIG. 5 shows a schematic diagram of a further embodiment of the method for provision PROV-TP of a therapy plan TP. In this embodiment, the model may include a trained function TF. At least one parameter of the trained function TF may further be adjusted by a comparison of a training therapy plan with a comparison therapy plan.

[0157] Shown schematically in FIG. 6 is an embodiment of a computer-implemented method for provision PROV-TF of a trained function TF. In a first act, a preacquired first training dataset TDS1 may be received REC-TDS1. In this case, the first training dataset TDS1 may map an examination object including a first tissue area TA1 at at least one first point in time. In a second act, a mapping of the first tissue area TA1 may be identified ID-TA1 in the first training dataset TDS1. In a third act, a preacquired second training dataset TDS2 may be received REC-TDS2. In this case, the second training dataset TDS2 may map the examination object including the first tissue area TA1 at at least one second point in time after the first point in time. In a fourth act, a further mapping of the first tissue area TA1 in the second training dataset TDS2 may be identified ID-TA1′ as the second training state TS2. In a fifth act, a comparison therapy plan VTP for a therapy apparatus may be received REC-VTP. In this case, the comparison therapy plan VTP may have at least one parameter for control of the therapy apparatus. Further, before the beginning of the method, between the at least one first point in time and the at least one second point in time, a change in the first tissue area TA1 may have been created by the therapy apparatus in accordance with the comparison therapy plan VTP. In a sixth act, a training therapy plan TTP for the therapy apparatus may be determined by applying the trained function TF to input data. In this case, the input data may be based on the first training dataset TDS1 and the second training state TS2. In a seventh act, at least one parameter of the trained function TF may be adjusted ADJ-TF by a comparison of the training therapy plan TTP with the comparison therapy plan VTP. Further, the training therapy plan TTP may be provided as output data of the trained function TF. In an eighth act, the trained function TF may be provided PROV-TF.

[0158] Shown schematically in FIG. 7 is an embodiment of a system. In this embodiment, the system may have a provision unit PRVS and a therapy apparatus. The therapy apparatus may further have an ultrasound unit UU. In this embodiment, the therapy apparatus may be embodied to create the change in the first tissue area TA1. The provision unit PRVS may further be configured to control the therapy apparatus (e.g., the ultrasound unit UU), in such a way with the aid of the therapy plan TP that the change is created between the at least one first point in time and the at least one second point in time in the first tissue area TA1. The provision unit PRVS may be embodied to control the therapy apparatus (e.g., the ultrasound unit UU) using a signal UU. S in accordance with the therapy plan TP.

[0159] In one embodiment, the ultrasound unit UU may have at least one transducer TD that is configured to emit the therapeutic ultrasound (e.g., an ultrasound field) in accordance with the therapy plan TP. Further, the ultrasound unit UU may have a coupling unit (not shown here), for example, with a tank that may be filled with a coupling medium (e.g., a liquid and/or a gel). The coupling unit may be configured to couple the at least one transducer TD to a surface of the examination object 31 acoustically. The at least one transducer TD (e.g., the coupling unit) may further be arranged on an examination object 31 (e.g., on a surface of the examination object 31). This enables the therapeutic ultrasound to be coupled through the surface of the examination object 31 (e.g., a skin surface) into the first tissue area TA1. In this case, the therapeutic ultrasound for this may be embodied to create at least one lesion in the first tissue area TA1 as the change. The examination object 31 may be arranged on a patient support apparatus 32.

[0160] The system may further have a medical C-arm x-ray device 37, for a medical imaging device for recording the dataset, for example. The medical C-arm x-ray device 37 may have a detector 34 (e.g., an x-ray detector) and an x-ray source 33. For recording the dataset, the arm 38 of the medical C-arm x-ray device 37 may be supported movably about one or more axes. The medical C-arm x-ray device 37 may further include a further movement unit 39 (e.g., a wheel system and/or rail system and/or a robot arm) that makes a movement of the medical C-arm x-ray device 37 in the room possible. The detector 34 and the x-ray source 34 may be fastened in a defined arrangement movably to a common C-arm 38.

[0161] To record the dataset of the examination object 31, the provision unit PRVS may send a signal 24 to the x-ray source 33. Thereafter, the x-ray source 33 may emit an x-ray bundle (e.g., a cone beam and/or fan beam and/or parallel beam). When the x-ray bundle (e.g., after an interaction with the examination object 31, such as the first tissue area TA1) strikes a surface of the detector 34, the detector 34 may send a signal 21 to the provision unit PRVS. The provision unit PRVS may receive the dataset with the aid of the signal 21.

[0162] The system may further include an input unit 42 (e.g., a keyboard) and/or a display unit 41 (e.g., a monitor and/or display). The input unit 42 may be integrated into the display unit 41 (e.g., with a capacitive and/or resistive input display). The input unit 41 may further be embodied for acquiring an input of a medical operator. For this, the input unit 42 may, for example, send a signal 26 to the provision unit PRVS. The display unit 41 may further be configured to display a graphical display of the dataset and/or of the therapy plan. For this, the provision unit PRVS may send a signal 25 to the display unit 41, for example.

[0163] Shown schematically in FIG. 8 is one embodiment of a provision unit PRVS. In this case, the provision unit PRVS may include an interface IF, a computing unit CU, and a memory unit MU. The provision unit PRVS may be configured to carry out a method for provision of a therapy plan PROV-TP and its aspects, in that the interface IF, the computing unit CU, and the memory unit CU are configured to carry out the corresponding method acts.

[0164] FIG. 9 shows a schematic diagram of one embodiment of a training unit TRS. The training unit TRS may include a training interface TIF, a training memory unit TMU, and a training computing unit TCU. The training unit TRS may be configured to carry out a method for provision of a trained function PROV-TF and its aspects, in that the training interface TIF, the training memory unit TMU, and the training computing unit TCU are configured to carry out the corresponding method acts.

[0165] The provision unit PRVS and/or the training unit TRS may, for example, involve a computer, a microcontroller, or an integrated circuit. As an alternative, the provision unit PRVS and/or the training unit TRS may involve a real or virtual network of computers (a technical term for a real network is Cluster, a technical term for a virtual network is Cloud). The provision unit PRVS and/or the training unit TRS may also be configured as a virtual system that is executed on a real computer or a real or virtual network of computers (e.g., virtualization).

[0166] An interface IF and/or a training interface TIF may involve a hardware or software interface (e.g., PCI bus, USB, or Firewire). A computing unit CU and/or a training computing unit TCU may have hardware elements or software elements (e.g., a microprocessor or a Field Programmable Gate Array (FPGA)). A memory unit MU and/or a training memory unit TMU may be realized as volatile memory (e.g., Random Access Memory (RAM)) or as permanent mass storage (e.g., hard disk, USB stick, SD card, Solid State Disk).

[0167] The interface IF and/or the training interface TIF may, for example, include a number of sub-interfaces that carry out different acts of the respective method. In other words, the interface IF and/or the training interface TIF may also be interpreted as a plurality of interfaces IF or a plurality of training interfaces TIF. The computing unit CU and/or the training computing unit TCU may, for example, include a number of sub-computing units that carry out different acts of the respective method. In other words, the computing unit CU and/or the training computing unit TCU may also be interpreted as a plurality of computing units CU or a plurality of training computing units.

[0168] The schematic diagrams shown in the described figures do not in any way depict a scale or a measure of size.

[0169] The methods and apparatuses described above in detail merely involve exemplary embodiments that may be modified by the person skilled in the art in a wide diversity of ways without departing from the field of the invention. Further, the use of the indefinite article “a” or “an” does not exclude the features concerned also being able to be present multiple times. Likewise, the terms “unit” and “element” do not exclude the components concerned consisting of a number of interacting subcomponents, which, where necessary, may also be spatially distributed.

[0170] The elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present invention. Thus, whereas the dependent claims appended below depend from only a single independent or dependent claim, it is to be understood that these dependent claims may, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or dependent. Such new combinations are to be understood as forming a part of the present specification.

[0171] While the present invention has been described above by reference to various embodiments, it should be understood that many changes and modifications can be made to the described embodiments. It is therefore intended that the foregoing description be regarded as illustrative rather than limiting, and that it be understood that all equivalents and/or combinations of embodiments are intended to be included in this description.