Medical imaging diagnostic device, medical information processing program, and medical information processing method

Abstract

To minimize unintended movement of medical imaging equipment by the operator. [Solution] The medical image diagnostic apparatus according to the embodiment comprises a first sensor unit, a first identification unit, a second sensor unit, a reading unit, an analysis unit, and a control unit. The first sensor unit detects contact by the operator. The first identification unit identifies the object to be operated on. The second sensor unit detects the operator's gestures. The reading unit reads the gestures based on the detection results of the second sensor unit. The analysis unit analyzes the instructions based on the reading results from the second sensor unit. The control unit controls the movement of the object to be operated on, which has been identified by the first identification unit, in a direction corresponding to the analysis results of the analysis unit.

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to a medical imaging diagnostic apparatus, a medical information processing program, and a medical information processing method.

Background Art

[0002] Conventionally, in order to move a part of a medical imaging diagnostic apparatus such as a bed apparatus or a gantry apparatus, an operator operates an input interface such as a push button provided on the gantry apparatus. The operator needs to go near the input interface provided on the gantry apparatus or the like to operate it. There is a known technique in which after an operator instructs an operation target by voice from a position away from the gantry apparatus or the like, the bed apparatus or the gantry apparatus is moved by a gesture. However, in the case of voice instructions, there is a possibility that voices of medical staff other than the operator or the subject may be misrecognized as the voice of the operator, and the bed apparatus or the gantry apparatus may move unintentionally by the operator.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce the unintentional movement of the medical imaging diagnostic apparatus by the operator. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problems. The problems corresponding to the respective effects of the respective configurations shown in the embodiments described later can also be positioned as other problems. <00ffff

Means for Solving the Problems

[0005] The medical image diagnostic apparatus according to this embodiment comprises a first sensor unit, a first identification unit, a second sensor unit, a reading unit, an analysis unit, and a control unit. The first sensor unit detects contact by the operator. The first identification unit identifies the object to be operated on. The second sensor unit detects the operator's gestures. The reading unit reads the gestures based on the detection results of the second sensor unit. The analysis unit analyzes the instructions based on the reading results from the second sensor unit. The control unit controls the movement of the object to be operated on, which has been identified by the first identification unit, in a direction corresponding to the analysis results of the analysis unit. [Brief explanation of the drawing]

[0006] [Figure 1] Figure 1 is a block diagram showing a part of the configuration of an X-ray CT apparatus according to the first embodiment. [Figure 2] Figure 2 is a block diagram showing an example of the configuration of the control device according to the first embodiment. [Figure 3] Figure 3 shows an example of a marker according to the first embodiment. [Figure 4] Figure 4 shows an example of a marker according to the first embodiment. [Figure 5] Figure 5 shows an example of a marker according to the first embodiment. [Figure 6] Figure 6 shows an example of the positional relationship between the camera and the marker according to the first embodiment. [Figure 7] Figure 7 shows an example of the positional relationship between the camera and the marker according to the first embodiment. [Figure 8] Figure 8 shows an example of the placement of the contact sensor according to the first embodiment. [Figure 9] Figure 9 shows an example of the placement of the contact sensor according to the first embodiment. [Figure 10] Figure 10 is a flowchart showing an example of processing performed in the processing circuit of the control device according to the first embodiment. [Figure 11] Figure 11 shows an example of analyzing the inclination angle in a modified version of the first embodiment. [Figure 12]Figure 12 is a block diagram showing an example of the configuration of a control device according to the second embodiment. [Figure 13] Figure 13 is a flowchart showing an example of processing performed in the processing circuit of the control device according to the second embodiment. [Figure 14] Figure 14 is a flowchart showing an example of processing performed in the processing circuit of the control device according to the third embodiment. [Figure 15] Figure 15 is a block diagram showing an example of the configuration of a control device according to a modified example of the third embodiment. [Figure 16] Figure 16 is a flowchart showing an example of the display processing of a monitor according to a modified example of the third embodiment. [Modes for carrying out the invention]

[0007] The following describes the medical image diagnostic apparatus, medical information processing program, and medical information processing method according to each embodiment, with reference to the drawings.

[0008] A medical imaging diagnostic device is a single modality such as an X-ray CT (Computed Tomography) device, an MRI (Magnetic Resonance Imaging) device, a PET (Positron Emission Tomography) device, and a SPECT (Single Photon Emission Computed Tomography) device. Alternatively, a medical imaging diagnostic device may be a composite modality such as a PET-CT device, a SPECT-CT device, and a PET-MRI device. In the following description, the medical imaging diagnostic device in each embodiment will be described as an X-ray CT device, but each embodiment is not limited to an X-ray CT device. It can be similarly implemented with the various medical imaging diagnostic devices described above.

[0009] (First embodiment) A first embodiment will be described. In this embodiment, the X-ray CT apparatus identifies the target to be operated based on the detection result of contact between a first sensor unit that detects contact by the operator and the operator, reads the gesture based on the detection result of a second sensor unit that detects the operator's gesture, analyzes the instruction content based on the reading result, and controls the identified target to move in the direction according to the analysis result. The operator's gesture refers to the movements and gestures of the operator's hands. Also, "reading the gesture" means obtaining the reading result. The reading result is information such as the position of the operator's arms or legs or objects attached to the operator, the amount of change in position, and acceleration. The reading result may be part of the time-series information, or it may be information such as the position, the amount of change in position, and acceleration at a certain point in time. The operator is, for example, a radiological technologist, a clinical laboratory technologist, a doctor, a service engineer, etc., and is the person who operates the X-ray CT apparatus. In the first embodiment, the operation of the X-ray CT apparatus 1 will be described when there is only one operator, that is, when there is no one else in the examination room who could act as the operator.

[0010] Figure 1 is a block diagram showing an example of the configuration of an X-ray CT apparatus 1 according to the first embodiment. The X-ray CT apparatus 1 includes, for example, a pedestal 10, a patient bed 30, and a console 40. In Figure 1, for explanatory purposes, both a view of the pedestal 10 from the Z-axis direction and a view from the X-axis direction are shown, but in reality, there is only one pedestal 10. In this embodiment, the rotation axis of the rotating frame 17 in the non-tilted state or the longitudinal direction of the top plate 31 of the patient bed 30 is defined as the Z-axis direction, the axis perpendicular to the Z-axis direction and horizontal to the floor surface is defined as the X-axis direction, and the direction perpendicular to the Z-axis direction and perpendicular to the floor surface is defined as the Y-axis direction.

[0011] The mounting device 10 includes an X-ray tube 11, a wedge 12, a collimator 13, an X-ray high-voltage device 14, an X-ray detector 15, a DAS (Data Acquisition System) 16, a rotating frame 17, and a control device 18.

[0012] The X-ray tube 11 generates X-rays by irradiating thermoelectrons from the cathode (filament) toward the anode (target) by applying a high voltage from the X-ray high-voltage device 14. The X-ray tube 11 includes a vacuum tube. For example, the X-ray tube 11 is a rotating anode type X-ray tube that generates X-rays by irradiating thermoelectrons onto a rotating anode.

[0013] The wedge 12 is a filter for adjusting the amount of X-rays irradiated from the X-ray tube 11 to the subject P. Specifically, the wedge 12 is a filter that transmits and attenuates the X-rays irradiated from the X-ray tube 11 so that the X-rays irradiated from the X-ray tube 11 to the subject P have a predetermined distribution. For example, the wedge 12 is a wedge filter or a bow-tie filter, and is a filter formed by processing aluminum to have a predetermined target angle and a predetermined thickness.

[0014] The collimator 13 is a lead plate or the like for narrowing down the irradiation range of the X-rays that have passed through the wedge 12, and forms a slit by combining a plurality of lead plates or the like. Note that the collimator 13 may also be called an X-ray aperture.

[0015] The X-ray high-voltage device 14 has an electric circuit such as a transformer and a rectifier, and has a high-voltage generating device that has a function of generating a high voltage applied to the X-ray tube 11, and an X-ray control device that controls the output voltage according to the amount of X-rays irradiated by the X-ray tube 11. The high-voltage generating device 14 may be a transformer type or an inverter type. Note that the X-ray high-voltage device 14 may be provided on the rotating frame 17 described later, or may be provided on the fixed frame (not shown) side of the gantry device 10. The fixed frame is a frame that supports the rotating frame 17 rotatably.

[0016] The X-ray detector 15 detects X-rays irradiated from the X-ray tube 11 and passed through the subject P, and outputs an electrical signal corresponding to the amount of X-rays to the DAS 16. The X-ray detector 15 has, for example, multiple rows of X-ray detection elements arranged in the channel direction along a single arc centered on the focal point of the X-ray tube 11. The X-ray detector 15 has, for example, a structure in which multiple rows of X-ray detection elements, each arranged in the channel direction, are arranged in the slice direction (column direction, row direction). The X-ray detector 15 is also, for example, an indirect conversion type detector having a grid, a scintillator array, and a photosensor array.

[0017] A scintillator array has multiple scintillators, and each scintillator has a scintillator crystal that emits a photon amount of light corresponding to the amount of incident X-rays.

[0018] The grid is positioned on the X-ray incident side of the scintillator array and has an X-ray shielding plate that absorbs scattered X-rays. The grid is sometimes also called a collimator (one-dimensional collimator or two-dimensional collimator).

[0019] The optical sensor array has the function of converting the amount of light from a scintillator into an electrical signal, and includes optical sensors such as photodiodes and photomultiplier tubes.

[0020] The X-ray detector 15 may also be a direct conversion type detector having a semiconductor element that converts incident X-rays into an electrical signal.

[0021] The DAS16 includes an amplifier that amplifies the electrical signals output from each X-ray detection element of the X-ray detector 15, and an A / D converter that converts the electrical signals into digital signals, thereby generating detection data. The detection data generated by the DAS16 is transferred to the console device 40.

[0022] The rotating frame 17 is an annular frame that supports the X-ray tube 11 and the X-ray detector 15 facing each other, and rotates the X-ray tube 11 and the X-ray detector 15 by a control device 18, which will be described later. In addition to the X-ray tube 11 and the X-ray detector 15, the rotating frame 17 also supports an X-ray high-voltage device 14 and a DAS 16. Furthermore, the rotating frame 17 can also support various configurations not shown in Figure 1.

[0023] The detection data generated by DAS16 is transmitted via optical communication from a transmitter equipped with a light-emitting diode (LED) on the rotating frame 17 to a receiver equipped with a photodiode located on the non-rotating part of the mounting device 10, and then transferred to the console device 40, which will be described later. Contactless data transfer may also be employed.

[0024] Camera 101 is installed, for example, on the side of the stand 10. Camera 102 is installed on the ceiling of the examination room, facing the bed 30. Camera 102 photographs the operator and acquires the resulting images or videos as raw data. Cameras 101 and 102 may be placed anywhere in the examination room.

[0025] Cameras 101 and 102 are, for example, optical cameras, 3D cameras, infrared cameras, ultrasonic sensors, and terahertz cameras. Cameras 101 and 102 may be of the same type or different types. In addition to these, other cameras may be used besides cameras 101 and 102. On the other hand, there may be just one camera. Cameras 101 and 102 are examples of the second sensor unit.

[0026] The processing circuit 50 controls the operation of the entire X-ray CT apparatus 1. The system control function 51, preprocessing function 52, reconstruction processing function 53, and image processing function 54 of the processing circuit 50 are recorded in memory 41 in the form of programs that can be executed by a computer. The processing circuit 50 reads the programs from memory 41 and executes them to realize the functions corresponding to each program. In other words, the processing circuit 50, in the state in which each program has been read, will have the functions shown in the processing circuit 50 in Figure 1. The processing circuit 50 is implemented by, for example, a processor.

[0027] In Figure 1, the processing circuit 50 implements the system control function 51, preprocessing function 52, reconstruction processing function 53, and image processing function 54 using a single processor. However, the processing circuit 50 may also be configured by combining multiple independent processors, with each processor implementing each function of the processing circuit 50 by executing a program. Furthermore, although Figure 1 describes a single memory 41 storing programs corresponding to each processing function of the processing circuit 50, the processing circuit 50 may also be configured by distributing multiple memories 41 and reading the corresponding programs from individual memories 41.

[0028] The system control function 51 controls various functions of the processing circuit 50 based on input operations received via the input interface 43. The system control function 51 also controls the detection data collection process in the pallet apparatus 10 by issuing instructions to the X-ray high-voltage device 14, DAS 16, and patient table drive device 34, etc., via the control device 18. The system control function 51 also controls the operation of each part during positioning image acquisition and main imaging. Furthermore, the system control function 51 outputs information to memory 41 and memory 181 based on information received via the input interface 43.

[0029] The preprocessing function 52 generates data by applying preprocessing such as logarithmic transformation, offset correction, inter-channel sensitivity correction, and beam hardening correction to the detection data output from DAS16. Note that the data before preprocessing (detection data) and the data after preprocessing are sometimes collectively referred to as projection data.

[0030] The reconstruction processing function 53 generates CT image data by performing reconstruction processing on the projection data generated by the preprocessing function 52, using methods such as filtered back projection and iterative reconstruction. CT image data is sometimes referred to as a reconstructed image.

[0031] The image processing function 54 converts the CT image data generated by the reconstruction processing function 53 into tomographic image data of an arbitrary cross-section or 3D image data using a known method, based on input operations received from the user via the input interface 43. Note that the 3D image data may be generated directly by the reconstruction processing function 53.

[0032] Figure 2 is a block diagram showing an example of the configuration of the control device 18 according to the first embodiment. The configuration of the control device 18 will be explained using Figure 2.

[0033] The control device 18 includes, for example, a memory 181, a drive mechanism such as a motor and actuator (not shown), and a processing circuit 182 having a CPU (Central Processing Unit). The control device 18 receives input signals from an input interface 43 and a processing circuit 50 or processing circuit 182 attached to the console device 40 or the gantry device 10, and has the function of controlling the movement of the gantry device 10 and the patient bed device 30. However, the objects to be controlled are not limited to the gantry device 10 and the patient bed device 30, but may be any part of the X-ray CT apparatus 1.

[0034] The processing circuit 182, described later, identifies the target of operation based on the detection result of contact between the operator and the first sensor unit, which detects contact by the operator, reads the gesture based on the detection result of the second sensor unit, which detects the operator's gesture, analyzes the instruction content based on the reading result, and controls the identified target of operation to move in the direction according to the analysis result. For example, the control device 18 controls tilting the gantry device 10, moving the gantry device 10, and moving the patient device 30 and the tabletop 31. The patient device 30 moves in the X-axis direction or the Z-axis direction in Figure 1. The tabletop 31 also moves in the X-axis direction, the Y-axis direction or the Z-axis direction in Figure 1. The gantry device 10 also moves in the X-axis direction or the Z-axis direction. The patient device 30 may be fixed, and the gantry device 10 may move to perform imaging in a self-propelled gantry CT system. The gantry device 10 may also move across two examination rooms. The control device 18 may be installed on the mounting device 10 or on the console device 40.

[0035] Memory 181 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, a hard disk, and an optical disk. Memory 181 stores, for example, a specified target for operation, the instructions given by the operator regarding direction, and data on the shooting range (Field of View: FOV) used when capturing positioning images and setting shooting conditions. This data may be stored by the control device 18 in a communicable external memory instead of (or in addition to) memory 181. The external memory is, for example, memory 41.

[0036] The processing circuit 182 controls the movement of the frame device 10 and the bed device 30. The contact detection function 182a, target identification function 182b, gesture reading function 182c, gesture analysis function 182d, and control signal generation function 182e of the processing circuit 182 are recorded in memory 181 in the form of a program that can be executed by a computer. Details of each function will be described later. The processing circuit 182 realizes the function corresponding to each program by reading the program from memory 181 and executing it. In other words, the processing circuit 182 in the state in which each program has been read has the functions shown in the processing circuit 182 in Figure 2. The processing circuit 182 is realized by a processor, for example.

[0037] In Figure 2, the processing circuit 182 implements the following processing functions using a single processor: contact detection function 182a, target identification function 182b, gesture reading function 182c, gesture analysis function 182d, and control signal generation function 182e. However, the processing circuit 182 may also be configured by combining multiple independent processors, with each processor executing a program to implement each function of the processing circuit 182. Furthermore, although Figure 2 describes a single memory 181 storing programs corresponding to each processing function of the processing circuit 182, multiple memories 181 may be distributed and arranged. The processing circuit 182 may also be configured to read the corresponding programs from individual memories 181.

[0038] In the above explanation, the term "processor" refers to circuits such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), or a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), or a Field Programmable Gate Array (FPGA)). If the processor is a CPU, for example, it performs its functions by reading and executing a program stored in memory 181. On the other hand, if the processor is an ASIC, instead of storing the program in memory 181, the function is directly incorporated as a logic circuit within the processor's circuitry.

[0039] The contact detection function 182a is a function that detects contact between the contact sensor 35 and the operator based on the contact signal output by the contact sensor 35. For example, the contact detection function 182a acquires a contact signal indicating that the bed contact sensor 352, which is provided on the bed device 30, has detected contact between the contact sensor 35 and the operator. The contact detection function 182a is also an example of a contact detection unit. The bed contact sensor 35 will be described later.

[0040] The target identification function 182b identifies the target of operation corresponding to the contact sensor 35 based on a contact signal indicating that contact between the contact sensor 35 and the operator has been detected by the contact detection function 182a. For example, the target identification function 182b identifies the target of operation as the bed device 30 based on a contact signal indicating contact between the bed contact sensor 352 provided on the bed device 30 and the operator. The target identification function 182b is an example of the first identification unit.

[0041] The gesture reading function 182c is a function that reads images or videos acquired from cameras 101 and 102. For example, the gesture reading function 182c acquires raw image or video data including the contact sensor 35 and the operator from camera 101, which is installed on the mounting device 10, and camera 102, which is suspended from the ceiling of the examination room, and generates a reading result. The reading result is, for example, information that associates 3D position information with time. Furthermore, the gesture reading function 182c stores the reading result in memory 181. The gesture reading function 182c is an example of a reading unit.

[0042] The gesture analysis function 182d is a function that analyzes the reading results from the gesture reading function 182c. For example, the gesture analysis function 182d generates an analysis result from the reading result that indicates the direction indicated by the operator, that is, the direction in which the object to be moved will be moved. However, the object to be analyzed is not limited to hand movements, but may also be the movement of the entire arm. The gesture analysis function 182d only needs to analyze the movement that indicates which direction the operator is indicating. In addition, the gesture analysis function 182d may also analyze the number of fingers that the operator is holding up. The gesture analysis function 182d is an example of the analysis unit.

[0043] The control signal generation function 182e generates control signals that control the operation based on the target object and the direction in which the target object is moved. It may also generate control signals that change the speed of the target object according to the number of fingers analyzed by the gesture analysis function 182d. For example, if the operator holds up many fingers, the control signal generation function 182e generates a control signal that increases the speed. The control signal generation function 182e is an example of a control unit. By changing the speed according to the number of fingers held up, the target object can be moved at the speed intended by the operator, allowing for efficient positioning of the subject.

[0044] Figures 3, 4, and 5 show examples of markers according to the first embodiment. Here, using Figures 3, 4, and 5, an example of the process by which the gesture analysis function 182d analyzes the direction indicated by the operator will be explained.

[0045] The gesture analysis function 182d analyzes the direction indicated by the operator by calculating the relative positions of a center marker indicating the center position and an indicator marker indicating the direction. The relative position is the position of the indicator marker relative to the center marker. For example, Figure 3 is an example of a glove with two markers. This glove has, for example, a red center marker 2A at the position of the thenar eminence and a blue indicator marker 1A near the tip of the index finger. The gesture analysis function 182d can distinguish between a center marker and an indicator marker based on the color of the marker. In the case of Figure 3, the gesture analysis function 182d analyzes that the operator is indicating upward movement of the object being operated on because the indicator marker 1A is positioned above the center marker 2A.

[0046] Furthermore, for example, Figure 4 shows an example of a glove with two markers. This glove has, for example, a band-shaped center marker 2B attached to the thenar eminence and a band-shaped indicator marker 1B attached to the index finger. The gesture analysis function 182d can determine whether a marker is a center marker or an indicator marker based on its area and size. Similarly, Figure 5 shows another example of a glove with two markers. This glove has, for example, a star-shaped center marker 2C attached to the thenar eminence and a triangular indicator marker 1C attached to the index finger. The gesture analysis function 182d can determine whether a marker is a center marker or an indicator marker based on its shape.

[0047] The color and shape of the attached objects do not need to differ between the center marker and the indicator marker, and are not limited to the examples in Figures 3, 4, and 5. Attached objects include, for example, gloves and markers. The operator may wear gloves with the center marker attached, or they may directly attach a sticker or similar marker to their hand.

[0048] Figure 6 shows an example of the positional relationship between the camera and the marker according to the first embodiment. In Figure 6, for example, the center marker 2A and the indicator marker 1A are located on an axis parallel to the Z-axis direction and passing through the camera 101. Therefore, in the image from camera 101 acquired by the gesture reading function 182c, the center marker 2A and the indicator marker 1A overlap, making it impossible to obtain the relative position of the indicator marker 1A with respect to the center marker 2A. The camera 102 in Figure 6 is, for example, a wide-angle camera, and the double-headed arrow 102b sandwiched between two dotted lines 102a indicates the field of view of camera 102. The gesture reading function 182c acquires an image taken from the Y-axis direction by camera 102, analyzes the image from camera 102, and generates information that the indicator marker 1A is in a positive position in the Z-axis direction relative to the center marker 2A.

[0049] Figure 7 shows an example of the positional relationship between the camera and the marker according to the first embodiment. In Figure 7, for example, the center marker 2A and the indicator marker 1A are located on the opposite side from the surface on which the camera 101 is installed. Therefore, in the image from camera 101 acquired by the gesture reading function 182c, the indicator marker 1A and the center marker 2A are not visible, and the relative position of the indicator marker 1A with respect to the center marker 2A cannot be obtained. The camera 102 in Figure 7 is, for example, a wide-angle camera, and the double arrow 102b sandwiched between the two dotted lines 102a indicates the field of view of the camera 102. The gesture reading function 182c acquires an image taken from the Y-axis direction by camera 102. The gesture analysis function 182d analyzes the image from camera 102 and generates information that the indicator marker 1A is in a positive position in the Z-axis direction relative to the center marker 2A.

[0050] As shown in the examples in Figures 6 and 7, blind spots can be reduced and the range for reading gestures can be increased by installing multiple cameras. In particular, it is preferable to install the cameras so that they face in directions perpendicular to each other.

[0051] The gesture reading function 182c may acquire the output signal of an inertial sensor. Here, the output signal of the inertial sensor is an example of a reading result. The gesture analysis function 182d may, based on the reading result read by the gesture reading function 182c, identify the direction of movement of the object being controlled by the operator from the operator's hand movements, i.e., gestures. Inertial sensors include acceleration sensors, gyroscopes, motion sensors, etc. For example, if an acceleration sensor is attached to the glove worn by the operator, the gesture reading function 182c acquires time-series information of acceleration in the X-axis, Y-axis, and Z-axis directions in Figure 1. The gesture analysis function 182d analyzes which direction the operator is indicating based on the reading results of acceleration in the X-axis, Y-axis, and Z-axis directions. That is, an acceleration sensor can measure acceleration in the diagonal direction. Diagonal acceleration is the direction obtained by combining the vector components of the three axes: X-axis, Y-axis, and Z-axis. The acceleration sensor may also acquire directional information by combining the vector components of two of the X, Y, and Z axes.

[0052] Figure 8 shows an example of the arrangement of contact sensors according to the first embodiment. The contact sensors 35 are, for example, a tabletop contact sensor 351, a bed contact sensor 352, and a stand contact sensor 353. Figure 8 shows an example in which a bed contact sensor 352 is provided on the edge of the bed device 30, a tabletop contact sensor 351 is provided on the tabletop 31, and a stand contact sensor 353 is provided on the stand device 10. The tabletop contact sensor 351, bed contact sensor 352, and stand contact sensor 353 each output a contact signal that includes information indicating contact between the respective contact sensor and the operator. Furthermore, the tabletop contact sensor 351, bed contact sensor 352, and stand contact sensor 353 may also output the contact signal including ancillary information specific to each contact sensor. The target identification function 182b of the processing circuit 182 identifies the target of operation based on the ancillary information specific to the contact sensor included in the contact signal. The contact sensor 35, the tabletop contact sensor 351, the bed contact sensor 352, and the frame contact sensor 353 are examples of the first sensor unit. By providing contact sensors on each of the tabletop 31, the bed device 30, and the frame 20, which may be the targets of operation, the operator can determine the target of operation by touching the contact sensor corresponding to the target of operation. In other words, the operator can intuitively identify the target of operation. Furthermore, when the bed device 30 and the tabletop 31 are the targets of operation, by providing contact sensors on the bed device 30 and the tabletop 31, the target of operation can be identified without having to remain near the frame device.

[0053] Furthermore, the contact detection function 182a is configured not to acquire a contact signal when the subject touches the contact sensor 35. The contact detection function 182a detects contact between the operator and the tabletop contact sensor 351 or bed contact sensor 352 by receiving a contact signal indicating that the operator's gloves have come into contact with the tabletop contact sensor 351 or bed contact sensor 352. The contact detection function 182a may be configured not to acquire a contact signal when someone other than the operator wearing the gloves touches the tabletop contact sensor 351 or bed contact sensor 352. For example, this configuration can be realized using RFID (Radio Frequency Identification). For example, the gloves may further have an RF tag. Also, for example, the bed contact sensor 352 has a sensor that receives radio waves from the RF tag located at a predetermined distance. Therefore, when the RF tag on the gloves approaches the bed contact sensor 352, the contact detection function 182a can acquire a signal as a contact signal indicating that it has received radio waves from the RF tag. On the other hand, since the subject does not have an RF tag, the contact detection function 182a does not acquire a contact signal when the subject's hand approaches the bed contact sensor 352. In the above example, the system is configured not to acquire contact signals from anyone other than the operator.

[0054] Figure 9 shows an example of the arrangement of contact sensors according to the first embodiment. In Figure 9, the bed contact sensor 352, the tabletop contact sensor 351, and the frame contact sensor 353 are arranged side by side on the edge of the bed device 30. The arrangement of the contact sensors 35 is not limited to that shown in Figures 8 and 9. In addition, a contact sensor 35 may be provided for each object being operated. The surface of the contact sensor 35 may be covered with a replaceable material such as a protective sheet. If the surface of the contact sensor 35 becomes dirty, the protective sheet or the like can be replaced to keep the surface of the contact sensor 35 clean.

[0055] In addition to a contact sensor, a proximity sensor may be used to acquire a contact signal for identifying the target object. A proximity sensor is a non-contact sensor that detects the presence of an object by detecting the reflection of light, sound waves, radio waves, etc. To prevent the operator from acquiring an unintended contact signal using the proximity sensor, the proximity sensor detects the presence of an object at a sufficiently close distance. A sufficiently close distance is, for example, 9 to 15 mm. A sufficiently close distance may be shorter than 9 mm. Furthermore, the contact detection function 182a detects when the glove worn by the operator approaches the proximity sensor, so as not to detect the approach of an object other than the operator. The proximity sensor is an example of the first sensor unit.

[0056] Figure 10 is a flowchart showing an example of processing in the processing circuit 182 of the control device 18 in Figure 1, according to the first embodiment. Here, an example of processing in the processing circuit 182 of the first embodiment will be explained using Figure 10. In the flowchart of Figure 10, as shown in Figure 6, a center marker and an indicator marker are arranged, and an example is used in which the operator is indicating the +Z axis direction.

[0057] (Step S103) The control signal generation function 182e of the processing circuit 182 generates a signal that controls the processing circuit 182 to an input-disabled state, where it does not accept input from the operator. The input-disabled state is a state set for each object being operated on, in which the operator's input is not accepted. Operator input refers to information such as the direction indicated by a gesture.

[0058] (Step S105) The contact detection function 182a of the processing circuit 182 detects which object the operator has touched. For example, the contact detection function 182a acquires a contact signal from the top plate contact sensor 351 provided on the top plate 31. If the contact detection function 182a acquires a contact signal, the process proceeds to step S107. If the contact detection function 182a does not acquire a contact signal, the process proceeds to step S103.

[0059] (Step S107) The target identification function 182b of the processing circuit 182 identifies the target of operation based on the result of the contact signal acquired by the contact detection function 182a. For example, based on the result of the contact detection function 182a acquiring the contact signal from the top panel contact sensor 351, the target identification function 182b identifies the top panel 31 as the target of operation. The target identification function 182b stores the identified target of operation in the memory 181.

[0060] (Step S109) The control signal generation function 182e of the processing circuit 182 generates a signal that controls the system to enter an input-enabled state, which allows it to accept input from the operator. The input-enabled state is a state set for each target system that allows it to accept input from the operator.

[0061] (Step S111) If the contact detection function 182a of the processing circuit 182 continues to detect contact, this process proceeds to step S113. If the contact detection function 182a of the processing circuit 182 stops detecting contact, this process proceeds to step S121. For example, the process proceeds to step 121 the moment the contact detection function 182a stops detecting contact. Alternatively, for example, this process may proceed to step 121 5 seconds after the contact detection function 182a stops detecting contact. The time elapsed since contact detection stopped is not limited to 5 seconds; it could be 10 seconds or a certain period of time.

[0062] (Step S113) While contact is detected by the contact detection function 182a, the gesture reading function 182c of the processing circuit 182 reads images or videos acquired from cameras 101 and 102. For example, the gesture reading function 182c reads images or videos acquired from camera 101, which is mounted on the stand device 10, and camera 102, which is suspended from the ceiling of the inspection room, and stores them in the memory 181.

[0063] (Step S115) The gesture analysis function 182d of the processing circuit 182 analyzes the operator's gestures based on the results read by the gesture reading function 182c. For example, the gesture analysis function 182d analyzes that the hand movement shown in the image or video stored in memory 181 indicates the +Z axis direction. The gesture analysis function 182d stores the instruction given by the operator regarding the direction in memory 181.

[0064] (Step S117) The control signal generation function 182e of the processing circuit 182 generates a signal to control the movement of the target object according to the instructions, based on the information of the target object and the information of the instructions stored in the memory 181. For example, the control signal generation function 182e generates a control signal to control the movement of the top plate 31 in the +Z axis direction.

[0065] (Step S119) The X-ray CT apparatus 1 receives a control signal generated in step S117 and sends it to the patient table apparatus 30, controlling the identified object to move in a direction corresponding to the analysis results. For example, the top plate 31 of the X-ray CT apparatus 1 moves in the +Z axis direction. After step S119, the process proceeds to step S111.

[0066] (Step S121) The control signal generation function 182e of the processing circuit 182 generates a signal that controls the system to an input-disabled state, where it does not accept input from the operator.

[0067] Step S111 may be performed in place of step S111, or in addition to step S111, between steps S113 and S115, between steps S115 and S117, or between steps S117 and S119.

[0068] The control signal generation function 182e generates a control signal that, based on the instructions given by the operator, controls the top plate 31 on which the subject is placed to move to the starting position for imaging, so as not to collide with the stand device 10.

[0069] Each object to be moved is equipped with a contact sensor, allowing the operator to intuitively identify the object they wish to move by touching the sensor. Additionally, a camera is provided, enabling the operator to intuitively control the direction of movement of the object through gestures.

[0070] Instructing the target of movement based on the output signal of the contact sensor 35, and instructing the direction of movement by reading gestures, is an operation that involves confirmation by the operator. Therefore, for example, it is possible to reduce malfunctions in the movement of the bed device 30.

[0071] The operator can move freely without having to remain in the position where the push buttons for moving the bed device 30, the tabletop 31, and the stand device 10 are located. Furthermore, because the operator can move freely, they can assist the subject while adjusting the position.

[0072] (Modified version of the first embodiment) Figure 11 shows an example of analyzing the tilt angle according to a modified version of the first embodiment. The gesture analysis function 182d analyzes whether the operator is instructing the movement of the rigging device 10 or instructing the tilt control of the rigging device 10, when the object of operation is the rigging device 10. For example, the operator attaches a tilt reference marker 3A to their elbow to indicate the tilt reference. The straight line at the time the tilt starts is denoted as t1, and the straight line at the time the tilt ends is denoted as t2. The arm tilt 400 shows the trajectory from the start to the end of the tilt. The gesture analysis function 182d calculates the angle that the straight line connecting the center marker 2A and the tilt reference marker 3A makes with the XZ plane and stores it in the memory 181. The control signal generation function 182e generates a control signal to tilt the rigging device 10 based on the information of the angle between the straight line t1 and the XZ plane at the time the tilt starts, and the information of the angle between the straight line t2 and the XZ plane at the time the tilt ends. The straight line connecting the markers may, for example, be the straight line connecting the indicator marker 1A and the tilt reference marker 3A, or the straight line connecting the indicator marker 1A and the center marker 2A.

[0073] (Second embodiment) A second embodiment will now be described. In the second embodiment, the operation of the X-ray CT scanner when there are multiple potential operators in the examination room will be described. The X-ray CT scanner according to this embodiment detects operator contact, identifies the target of operation, identifies the operator, detects and reads the operator's gestures, analyzes the direction to indicate, and controls the target of operation. Furthermore, the X-ray CT scanner according to this embodiment enters an input permission state when it obtains a contact detection result, and enters an input restriction state when it cannot obtain a contact detection result. In this embodiment, the person among the potential operators who actually performs the operation is referred to as the operator.

[0074] The following description of the second embodiment will mainly focus on the differences from the first embodiment. Furthermore, components similar to those in the first embodiment will be denoted by the same reference numerals, and their descriptions may be omitted.

[0075] Figure 12 is a block diagram showing an example of the configuration of a rigging device according to the second embodiment. The processing circuit 192 included in the control device 19 of the X-ray CT apparatus according to this embodiment further includes an operator identification function 192f. This differs from the control device 18 of the X-ray CT apparatus 1 according to the first embodiment shown in Figure 2.

[0076] The operator identification function 192f is a function that identifies the operator responsible for identifying the target object and providing direction instructions when there are multiple potential operators in the examination room. For example, the operator identification function 192f identifies the operator candidate wearing the glove or marker first detected by the contact detection function 192a as the operator. In other words, the operator identification function 192f identifies the operator candidate who makes contact with the target object to enable input as the operator. The operator identification function 192f is an example of a second identification unit.

[0077] The operator identification function 192f may identify the operator candidate from the images or videos of camera 101 and camera 102 by image recognition, and the identified person may be designated as the operator. The operator identification function 192f may also identify the operator by image recognition of the operator's facial features, or by identifying the operator from a glove or marker visible in the image or video.

[0078] The contact detection function 192a, target identification function 192b, gesture reading function 192c, gesture analysis function 192d, control signal generation function 192e, and operator identification function 192f of the processing circuit 192 are recorded in memory 191 in the form of a program that can be executed by a computer. The contact detection function 192a, target identification function 192b, gesture reading function 192c, and gesture analysis function 192d have the same functions in this embodiment as in the first embodiment, so their description is omitted. From here, the operator identification function 192f will be described, and the differences between the control signal generation function 192e in this embodiment and the control signal generation function 182e in the first embodiment will be explained.

[0079] The control signal generation function 192e generates a control signal that prevents the gesture analysis function 192d from analyzing gestures made by anyone other than the operator identified by the operator identification function 192f. The gesture analysis function 192d, upon receiving this control signal, does not analyze gestures made by anyone other than the operator. Furthermore, similar to the first embodiment, the control signal generation function 192e has the function of generating a control signal that controls based on the object to be operated and the direction in which the object to be moved is moved.

[0080] Figure 13 is a flowchart showing an example of processing performed in the processing circuit of the control device according to the second embodiment. Here, an example of processing performed in the processing circuit 192 of the second embodiment will be described using Figure 13. Note that the difference from the first embodiment is step S211.

[0081] (Step S211) The operator identification function 192f of the processing circuit 192 identifies an operator from among multiple operator candidates. The operator identification function 192f stores the information of the identified operator in the memory 191. In this way, the operator identification function 192f continues to identify the operator candidate who is maintaining contact as the operator while steps S213 to S221 are repeated.

[0082] In step S211, based on the operator information stored in memory, in step S217, the gesture analysis function 192d analyzes the gestures of the identified operator.

[0083] Step S213 may be performed in place of or in addition to step S213 between any one of the following steps: between step S209 and step S211, between step S215 and step S217, between step S217 and step S219, or between step S219 and step S221.

[0084] A motion glove for identifying the target of movement and a direction glove for indicating direction may be hardwired together. Alternatively, the motion glove and the direction glove may be connected by bioelectricity. For example, electrodes may be provided on the operator's glove. Each electrode has the function of inputting and outputting muscle current. Connecting the motion glove and the direction glove can achieve a highly reliable configuration. This is not limited to cases where there are multiple potential operators. Even when there is only one operator, the motion glove and the direction glove may be connected.

[0085] (Third embodiment) A third embodiment will now be described. Unlike the second embodiment, in the third embodiment, the X-ray CT apparatus according to this embodiment will switch to an input-enabled state when it obtains a detection result of contact between the contact sensor and the operator while in an input-disabled state, and will switch to an input-disabled state when it obtains another detection result of contact between the contact sensor and the operator while in an input-enabled state. If the X-ray CT apparatus cannot obtain a detection result of contact, it will remain in either the input-enabled state or the input-disabled state.

[0086] The following description of the third embodiment will mainly focus on the differences from the first or second embodiment. Furthermore, components similar to those in the first or second embodiment will be denoted by the same reference numerals, and their descriptions may be omitted.

[0087] Figure 14 is a flowchart showing an example of processing performed in the processing circuit of the control device according to the third embodiment. Here, an example of processing performed in the processing circuit 192 of the third embodiment will be described using Figure 14. Note that the differences from the first embodiment are steps S305, S311, and S313.

[0088] (Step S305) The contact detection function 192a of the processing circuit 192 detects which operating object the operator has touched. If a contact signal is acquired when the input is disabled, the process proceeds to step S307. If the contact detection function 192a does not acquire a contact signal, the process proceeds to S303. Acquiring a contact signal when the input is disabled is one example of acquiring the first detection result.

[0089] (Step S311) The operator identification function 192f of the processing circuit 192 identifies the operator from among the candidate operators based on the images or videos from cameras 101 and 102. In S305, the operator identification function 192f identifies the candidate operator who touched the contact sensor when input was disabled as the operator. The operator identification function 192f stores the information of the identified operator in the memory 191.

[0090] (Step S313) If the contact detection function 192a of the processing circuit 192 acquires a contact signal while the input is enabled, this process proceeds to step S323. If the contact detection function 192a of the processing circuit 192 does not acquire a contact signal, this process proceeds to step S315. Acquiring a contact signal while the input is enabled is one example of acquiring a second detection result.

[0091] In step S311, based on the operator information stored in memory, in step S317, the gesture analysis function 192d analyzes the gestures of the identified operator.

[0092] Step S313 may be performed in place of or in addition to step S313 between any one of the following steps: between step S309 and step S311, between step S315 and step S317, between step S317 and step S319, or between step S319 and step S321.

[0093] When multiple potential operators are present in the examination room, the X-ray CT scanner reads and analyzes the gestures of the operator who identifies the object to be operated on and directs its direction. Even when multiple potential operators are present in the examination room, the X-ray CT scanner can reduce the likelihood of malfunctions such as reading and analyzing the gestures of someone who should not be giving instructions.

[0094] (Modified version of the third embodiment) A modification of the third embodiment will now be described. In the modification of the third embodiment, an example of what is displayed on the monitor will be described. Note that in the first and second embodiments as well, a monitor may be provided and the information of the identified operator, the information of the identified object of operation, the information of the direction to indicate, etc., may be displayed on the monitor.

[0095] The following description of a modified example of the third embodiment will mainly focus on the differences from the third embodiment. Furthermore, components similar to those in the third embodiment will be denoted by the same reference numerals, and their descriptions may be omitted.

[0096] Figure 15 is a block diagram showing an example of the configuration of an X-ray CT apparatus according to a modified example of the third embodiment. The processing circuit 202 included in the control device 20 of the X-ray CT apparatus according to this embodiment further includes a display signal generation function 202g. In addition, the stand device 10a of the X-ray CT apparatus according to this embodiment further includes a monitor 103. This differs from the control device 19 of the first and second embodiments. However, the monitor 103 may also be provided in the first and second embodiments.

[0097] The monitor 103 is installed on the stand device 10a and displays recognition information using signals generated by the display signal generation function 202g of the processing circuit 202. Recognition information includes operator information, information about the object being operated on, and information about the direction to indicate. For example, the monitor 103 displays operator information, information about the object being operated on, and information about the direction to indicate. The monitor 103 may also be installed on the bed device 30. Alternatively, the monitor 103 may be installed in any location in the examination room. Not limited to the monitor 103, lighting equipment may also be provided to display operator information, information about the object being operated on, and information about the direction to indicate. The monitor 103 and lighting equipment are examples of display units.

[0098] The display signal generation function 202g generates a display signal that displays recognition information, such as operator information, information about the object being operated, and information about the direction to indicate. Operator information includes the name, face, and a color associated with each operator of the X-ray CT scanner. For example, the display signal generation function 202g generates a display signal that displays the operator's name, face, and a color associated with each operator on the monitor 103. The display signal generation function 202g may also generate a display signal that displays predetermined colors and light emission patterns for each candidate operator on lighting equipment installed on the patient bed device 30 or the stand device 10a. The display signal generation function 202g may also display information associated with the operator based on the color and light emission pattern displayed on the lighting equipment. Lighting equipment includes, for example, incandescent light bulbs, fluorescent lamps, LEDs (Light Emission Diodes), etc. For example, the lighting equipment may also be an electronic display board that displays characters or pictures using light emission patterns. Furthermore, even when there is only one operator in the first embodiment, the display signal generation function 202g may generate a display signal to display recognition information. Also, the display signal generation function 202g is an example of a display unit.

[0099] Figure 16 is a flowchart showing an example of processing performed in the processing circuit of the control device according to a modified example of the third embodiment. Here, an example of processing performed in the processing circuit 202 of the modified example of the third embodiment will be described using Figure 16. Note that the differences from the third embodiment are steps S419, S421, and S429.

[0100] (Step S419) The display signal generation function 202g of the processing circuit 202 generates a display signal that displays the information of the identified target, the identified operator, and the analyzed instruction content stored in the memory 201.

[0101] (Step S421) The monitor 103 displays information about the identified target of operation, information about the operator, and information about the instruction content based on the display signal generated in step S419.

[0102] (Step S429) The gesture analysis function 202d of the processing circuit 202 analyzes the reading result from the gesture reading function 202c. For example, the gesture analysis function determines whether or not there is a candidate operator in the examination room. If there is a candidate operator in the examination room, the process proceeds to step S405. If there is no candidate operator in the examination room, the process terminates.

[0103] In step S429, the process may be terminated if the power to the X-ray CT scanner is turned off. If the power to the X-ray CT scanner is on, the process may proceed to step S405. The process may also be terminated if the X-ray CT scanner is taking an image. The process may proceed to step S405 if the X-ray CT scanner has not yet taken an image.

[0104] Step S413 may be performed between any of the following processes: steps S409 and S411, steps S415 and S417, steps S417 and S419, steps S421 and S423, or steps S423 and S425.

[0105] The display signal generation function 202g generates a signal which allows the monitor 103 to display at least one piece of information: operator information, information about the object being operated, and the direction being indicated. This allows users to confirm who the operator is, which object is being operated, and which direction is being indicated.

[0106] When the technical concept of this embodiment is realized in a medical information processing method, the medical information processing method identifies the target to be operated based on the detection result of contact between the operator and a first sensor unit that detects contact by the operator, reads the gesture based on the detection result of the operator's gesture from a second sensor unit that detects the operator's gesture, analyzes the instruction content based on the reading result, and controls the identified target to move in the direction corresponding to the analysis result. The processing procedure and effects of the medical information processing method are the same as in the embodiment, so a description is omitted.

[0107] When the technical concept of this embodiment is implemented in a medical information processing program, the medical information processing program enables the computer to: identify the target of operation based on the detection result of contact between the operator and a first sensor unit that detects contact by the operator; read the operator's gesture based on the detection result of a second sensor unit that detects the operator's gesture; analyze the instruction content based on the reading result; and control the identified target of operation to move in the direction corresponding to the analysis result. The processing procedure and effects in the medical information processing program are the same as in the embodiment, so a description is omitted.

[0108] According to at least one embodiment described above, the medical imaging diagnostic device can reduce unintended movement of the medical imaging diagnostic device by the operator.

[0109] While several embodiments have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be carried out in a variety of other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0110] 1 X-ray CT device 10. Mounting device 18 Control device 30 Bed equipment 35 Contact Sensor 1A Indicator Marker 1B Indicator Marker 1C Indicator Marker 2A Center Marker 2B Center Marker 2C Center Marker 3A Tilt Reference Marker 101 Camera 102 Cameras 103 Monitors 181 memory 182 Processing Circuit 182a Contact detection function 182b Target Identification Function 182c Gesture reading function 182d Gesture Analysis Function 182e Control signal generation function 192f Operator identification function 202g display signal generation function 351 Top panel contact sensor 352 Bed contact sensor 353 Mounting collision sensor 400 Arm Incline

Claims

1. A first sensor unit that detects contact by the operator, A first identification unit identifies the target of operation based on the detection result of contact between the first sensor unit and the operator, A second sensor unit that detects the operator's gestures, A reading unit reads the gesture based on the detection result of the second sensor unit, Based on the reading results from the aforementioned reading unit, an analysis unit analyzes the instruction content, A control unit that controls the movement of the object of operation specified in the first specific unit in a direction corresponding to the analysis result of the analysis unit, A medical imaging diagnostic device equipped with [a specific feature].

2. The medical image diagnostic apparatus according to claim 1, wherein the control unit performs control to stop the analysis by the analysis unit if it is unable to obtain a detection result that the first sensor unit and the operator have come into contact.

3. The medical image diagnostic apparatus according to claim 1, wherein the control unit, after acquiring a first detection result of contact between the first sensor unit and the operator, controls the analysis unit to stop the analysis when it acquires a second detection result of contact between the first sensor unit and the operator.

4. It further includes a second identification unit that identifies an operator from among multiple candidate operators, The medical image diagnostic apparatus according to claim 1, wherein the second sensor unit reads the gesture of the operator among the plurality of operator candidates.

5. The second sensor unit is a camera that captures an image including the operator and the first sensor. The medical image diagnostic apparatus according to claim 4, wherein the second identifying unit identifies the operator based on the image.

6. The first sensor unit detects the wearable object worn by the operator, The medical image diagnostic apparatus according to claim 4, wherein the second identification unit identifies the operator based on the detection result of the attached object by the first sensor unit.

7. The medical image diagnostic apparatus according to claim 1, further comprising a display unit that displays recognition information including at least one of the operator, the object of operation, and the direction corresponding to the analysis result.

8. The medical image diagnostic apparatus according to claim 7, wherein the display unit displays the recognition information using at least one of color, flashing, and illumination.

9. A center marker indicating the center position, A directional indicator marker, A recognition unit that recognizes the central marker and the indicator marker, Based on the recognition result by the recognition unit, an analysis unit analyzes the instruction content, A control unit controls the object to be operated on according to the above instructions, A medical imaging diagnostic device equipped with [a specific feature].

10. On the computer, Based on the detection result of contact between the first sensor unit, which detects contact by the operator, and the operator, the target of the operation is identified. Based on the detection result of the second sensor unit that detects the operator's gesture, the gesture is read. Based on the reading results, the instructions will be analyzed, This involves controlling the movement of the identified target object in a direction corresponding to the analysis results, A medical information processing program that makes this possible.

11. Based on the detection result of contact between the first sensor unit, which detects contact by the operator, and the operator, the target of the operation is identified. Based on the detection result of the second sensor unit that detects the operator's gesture, the gesture is read. Based on the reading results, the instructions are analyzed, The system controls the movement of the identified target object in the direction determined by the analysis results. Medical information processing method.

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