METHOD AND COMPUTER FOR PERMANENT MONITORING OF AN EXAMINATION ROOM

A monitoring method and system for monitoring a magnetic resonance apparatus having a scanner with an examination region, a video camera obtains images from an acquisition region that includes at least one of accesses to the examination room in which the scanner is situated, and a region upstream of the examination region. The images are evaluated in a processor to determine whether an alarm condition, which is different from only detecting a person, is met. When the alarm condition is met, the processor causes an alarm to be emitted that is perceptible within the examination room.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention concerns a monitoring method for an examination room in which a magnetic resonance system having an examination region, in particular an examination tunnel, is situated. The present invention also concerns a monitoring system and a non-transitory, computer-readable data storage medium that implements such a method.

The present invention also concerns an evaluation computer that implements such a monitoring.

The present invention also concerns an examination room, having a magnetic resonance (MR) system sutured therein, the MR system having an examination region, in particular an examination tunnel and wherein a video camera system is associated with the examination room, with which images are acquired from an acquisition region, wherein the acquisition region encompasses a region upstream of the examination region, and wherein the video camera system is connected to an evaluation computer.

Description of the Prior Art

An examination room of the above general type is known from DE 10 2015 211 148 A1 and from the corresponding US 2016 0 367 169 A1. With this examination room, images are acquired from the region upstream of the examination region during the course of preparation of an examination. A person is localized using the acquired images. Information can be projected onto particular body parts of the person as a function of the acquired localization.

Magnetic resonance systems often have a superconducting basic field magnet, which generates a high static basic magnetic field of for example 1.5 T or 3 T. The strong magnetic field attracts ferromagnetic objects with a correspondingly strong force. The magnetic field can impair the function of a cardiac pacemaker or a different implant. It can also result in ferromagnetic objects, which are accidentally brought into the region of the force field, being attracted by the force field. As a result, the ferromagnetic object can cause damage if it strikes objects or a person.

The owner/operator of the magnetic resonance system is obliged to train operating personnel of the magnetic resonance system appropriately so as to avoid such incidents, as well as to also post appropriate warning notices at the accesses to the (closed) examination room in which the magnetic resonance system is located. Nevertheless, accidents continue to occur due to untrained personnel or patients or relatives of patients, who enter the examination room and bring magnetizable objects with them, for example an oxygen cylinder, a ventilator, a wheelchair or, in the case of cleaning personnel, cleaning equipment or a floor polisher. The appropriate warning signs are either not seen or not observed. In some cases, the danger is underestimated by persons entering the room, despite cognition of the warning signs. In rare cases, accidents of this kind occur even with personnel who have been trained appropriately, if the training occurred a long time ago.

SUMMARY OF THE INVENTION

An object of the present invention is to provide a monitoring method and system which dangerous situations of this kind and accidents can be avoided as much as possible.

According to the invention, a monitoring method of the general type mentioned in the introduction makes use of an evaluation processor that, independently of operation of the magnetic resonance system, receives images of an acquisition region from a video camera system, wherein the acquisition region encompasses accesses to the examination room and/or a region upstream of the examination region. Whenever, in a standby mode, the evaluation processor detects a person in the received images, it checks whether an alarm condition different from just the detection of a person is met. Whenever the alarm condition is met, the evaluation processor changes into an alarm state in which, at least once, it emits at least one acoustic signal that is audible in the examination room, and/or emit an optical signal that is visible in the examination room, and otherwise maintains the standby mode. In the alarm state, the evaluation processor checks whether a termination command has been specified to it via a man-machine interface. Upon receipt of the termination command, the evaluation processor changes into an off-state in which it no longer emits the acoustic signal and/or the optical signal. In the alarm state and in the off-state, the evaluation processor checks whether it still detects the person in the images. Whenever it still detects the person in the alarm state and in the off-state, the evaluation processor maintains the current state and otherwise passes into the standby mode.

The video camera system and the evaluation processor are therefore inventively used not just during the course of operation of the magnetic resonance system (in other words, during the course of examinations and in the preliminary stage of such examinations), but operate more or less continuously. The evaluation processor firstly checks whether it detects a person at all. Detection of a person as such (per se) still does not trigger an alarm, however. Instead, an alarm is triggered only if an alarm condition is also met. The alarm condition is met if, using additional criteria aside from the “mere” detection of a person, it is detected that a dangerous situation could exist. In this case an acoustic signal and/or an optical signal is emitted as an output, in other words an appropriate warning.

In some cases the warning will be a false alarm. This is not critical, however, since in this case the false alarm can be ended by specifying the termination command.

The alarm condition can be configured in various ways.

For example, the alarm condition may be met only if, in addition to the person, the evaluation processor detects in the received images an object on the detected person that is different from the person and his or her clothing. Detection of the object is a necessary condition, but not imperatively an adequate one for meeting the alarm condition. It is possible for the detection of the object to already be adequate for changing to the alarm state, but it is not obligatory. For example, it is possible that the alarm condition is only met if the detected object adequately matches at least one predetermined object type. The object types can be specified as required to minimize the aforementioned risks. For example, the object types can be a cylinder (for example an oxygen cylinder), a chair (in particular a wheelchair), a watch and/or glasses. Other object types, such as a ventilator, a bed or a patient bed, a mop, a broom or motor-driven cleaning equipment are also conceivable.

Alternatively or additionally, the alarm condition may be met only if the detected person is in a predetermined section of the acquisition region. For example, the region of the magnetic resonance system which should be regarded as a “danger zone” can be determined in advance. In this case, a safety zone is also defined around the danger zone and this safety zone is also defined as a corresponding section of the acquisition region. In this case, the alarm condition is therefore only met if the detected person moves into the safety zone *thereby allowing the alarm to be emitted before the person is in the danger zone).

Alternatively or additionally, the alarm condition is met only if the detected person is a person different from at least one predetermined person. In this case, triggering of the acoustic signal can be limited to cases in which a person is detected who is not “known” to the evaluation processor as being authorized.

The evaluation processor can perform a 2D evaluation of the images acquired by the video camera system, but the evaluation processor preferably performs a 3D evaluation of the images acquired by the video camera system. Such a 3D evaluation also provides an item of depth information. As a result it is often easier to evaluate the region in which a person is situated and/or whether and possibly which, further object is detected on the person.

The alarm condition can be statically specified to the evaluation processor. In a preferred embodiment, the evaluation processor is designed as a self-learning system. In this case it is possible for the evaluation processor, when the termination command has been specified to it in the alarm state, to modify the alarm condition such that a situation, for which the alarm condition was previously regarded as having been met, to be removed from the alarm condition definition, or at least a lower weighting is associated with that situation.

The present invention also encompasses a non-transitory, computer-readable data storage medium encoded with programming instructions that, when loaded into a computer of a monitoring system, and possibly distributively loaded into other components of the monitoring system, cause the computer to operate the monitoring system in order to implement any or all embodiments of the method according to the invention as, described above.

The object is also achieved by a monitoring system of the type mentioned in the introduction wherein the acquisition region, alternatively or additionally to the region upstream of the examination region, encompasses accesses to the examination room, and the monitoring system has an evaluation processor according to the invention, as described above.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

According toFIGS. 1 and 2, an examination room1has walls2, a floor3and a ceiling4. The walls2can be transparent or non-transparent as required, for example partially glazed. At least one wall2has an access5to the examination room1, in other words, a door opening.

A magnetic resonance scanner6of a magnetic resonance system is situated in the examination room1. The magnetic resonance scanner6has an examination region7, for example an examination tunnel. The examination region7of the magnetic resonance scanner6is the region in which a temporally static, locally essentially homogeneous magnetic field (in practice usually called a B0 field) is generated by a basic field magnet8of the magnetic resonance scanner6. The B0 field has a high magnetic field strength, for example 1.5 T or more.

A video camera system9is associated with the examination room1. The video camera system9can be arranged inside the examination room1. Images B are acquired from an acquisition region by means of the video camera system9. The acquisition region comprises the accesses5to the examination room1and/or a region10upstream of the examination region7, for example the region in which an examination table11is located before introduction of the examination table11into the examination region7.

According toFIG. 2, the video camera system9is connected to an evaluation processor12. The evaluation processor12is programmed with a computer program13. The computer program13includes machine code14, which can be executed by the evaluation processor12. Execution of the machine code14by the evaluation processor12causes the evaluation processor12to carry out a monitoring method during operation, which will be illustrated in more detail below in connection withFIG. 3.

First, a state Z of the evaluation processor12according toFIG. 3is set to a standby mode Z1in a step S1. In the standby mode Z1the evaluation processor12receives a group of images B from the video camera system9in a step S2. The group of images B are those images B, which are acquired by the video camera system9at a particular instant. It is possible that the group is just a single image B. Alternatively, the group can comprise a number of images B.

In a step S3the evaluation processor12performs an evaluation of the received group of images B. It is possible that the evaluation processor12performs a 2D evaluation of the group of images B. The evaluation processor12preferably performs a 3D evaluation of the group of images, however. For example, an item of depth information can be determined from the respective image B for at least one of the acquired images B on the basis of a corresponding projection of a known pattern in the acquisition region. Alternatively, it is possible, by correlation of a number of images B, to determine a corresponding three-dimensional item of information. The relevant modes of procedure are generally known to persons skilled in the art.

In a step S4the evaluation processor12checks whether it detects a person15during the course of the evaluation. The detection of step S4should not be understood as meaning identification of the actual person15. It is therefore not a matter of whether a particular person15is detected (“that is Mr. Müller”), but whether a person15is detected at all (“there is someone here”). If the evaluation processor12detects a person15, the evaluation processor12moves to step S5. Otherwise it returns to step S2.

In step S5the evaluation processor12checks whether an alarm condition is met. The alarm condition is a condition different from detection of a person15per se. Detection of a person15per se, therefore, does not always or necessarily trigger an alarm, but an alarm is triggered only if in addition the alarm condition is met. Possible embodiments of the alarm condition will be illustrated in more detail below in connection with the further figures. If the alarm condition is met, the evaluation processor12moves to a step S6. Otherwise, it returns to step S2.

In step S6, the state Z of the evaluation processor12is set to an alarm state Z2. The evaluation processor12therefore moves into the alarm state Z2. In a subsequent step S7the evaluation processor12checks whether it is in the alarm state Z2. If this is the case, the evaluation processor12carries out step S8. Otherwise, step S8is skipped. In step S8the evaluation processor12emits an alarm signal A. The alarm signal A usually is an acoustic signal. Examples of suitable acoustic signals are a conventional alarm sound (sound of a horn, siren sound and the like) or the emitting of an appropriate spoken message, such as “Caution! There is a very strong magnetic field here. Go back immediately”. The acoustic signals can be emitted via a loudspeaker16(seeFIGS. 1 and 2). The acoustic device, via which the acoustic signal is output, —for example the loudspeaker16—is situated such that the acoustic signal can be heard in the examination room1.

Alternatively or additionally, the evaluation processor12emits an optical signal in step S8. For example, the evaluation processor12can switch on a yellow or red flashing light or, via a display device17, (seeFIGS. 1 and 2) show a text message, corresponding to the spoken message, to the person15. The optical device, via which the evaluation processor12emits the optical signal, is situated such that the optical signal is visible in the examination room1. For example, the display device17can be located in the region immediately upstream of the examination region7.

Step S9can follow step S8in which the evaluation processor12takes further measures, for example transmits appropriate messages to devices arranged remotely, so that emergency measures can be initiated there.

In step S10the evaluation processor12checks whether a termination command T has been specified to it via a human-machine interface18. If the termination command T is specified, the evaluation processor12moves to a step S11. In step S11the state Z of the evaluation processor12is set into an off-state Z3. Otherwise, the evaluation processor12skips step S11.

The evaluation processor12then receives a group of images B from the video camera system9in a step S12and evaluates the received group of images B in a step S13. Steps S12and S13correspond in terms of content to steps S2and S3.

In a step S14the evaluation processor12checks whether it does not detect a person during the course of the evaluation, in other words, no longer detects the person15. If the evaluation processor12continues to detect the person15, the evaluation processor12returns to step S7. Otherwise, it returns to step S1.

Due to the checking in step S7, the evaluation processor12therefore no longer emits the acoustic signal and/or the optical signal if it is in the off-state Z3.

It is possible that step S7as such is not present. In this case the evaluation processor12passes from step S14either to step S9(if present) or to step S10. In this case the alarm signal A is only emitted once during the transition from standby mode Z1into the alarm state Z2.

The approach ofFIG. 3is carried out independently of operation of the magnetic resonance scanner6, preferably “around the clock” (24/7). It is therefore in particular also carried out at times at which no examinations at all are to be performed with the magnetic resonance scanner6.

The alarm condition can, as already mentioned, be configured in different ways. Some of the possible embodiments will be illustrated in more detail below in connection withFIGS. 4 to 6.FIGS. 4 to 6therefore show possible embodiments of step S5ofFIG. 3.

According toFIG. 4, in one possible embodiment the evaluation processor12checks in step S21whether it detects a further object19on the person15in addition to the detected person15(wherein the clothing of the person15is regarded as a component of the person15). It is possible that the check of step S21is the only check. In this case the detection of the further object19as such decides whether the alarm condition is met or not. Detection of the further object19is in this case therefore not just a necessary condition, but also an adequate one for regarding the alarm condition as being met. The alarm condition corresponding to the diagram inFIG. 4is preferably only met, however if the detected object19sufficiently matches at least one predetermined object type. For example, according to the flowchart inFIG. 4it can be successively checked whether the detected object19has sufficient similarity to a bottle, a chair, a watch and/or glasses. The corresponding checks are shown inFIG. 4in steps S22to S25. Of course, not all illustrated checks have to be performed. Furthermore, as required, other or additional checks can also be made. Checking methods, by which corresponding object types can be detected, are generally known to those skilled in the art, and do not need to be described in more detail herein.

Furthermore, according to the flowchart inFIG. 5, it is possible for the evaluation processor12to check in step S31whether the detected person15is in a predetermined section20of the acquisition region. For example, it is possible that the alarm condition is still not met provided the detected person15is sufficiently far removed from the magnetic resonance scanner6and in particular the examination region7. If the detected person15moves into the predetermined section20by contrast, the alarm condition can be assumed to be met—with or without checking further conditions—and therefore the alarm can be triggered. The check according toFIG. 5can, as required, be combined with the check according toFIG. 4. For example, it is possible to carry out the two checks independently of each other, so that the alarm condition is already met, and one of the two checks is positive. Alternatively, it is possible to combine the two checks within the meaning of an AND operation, so that the alarm condition is only met if, firstly, the additional object19(optionally including object type) was detected and, furthermore, the person15is in the predetermined section20. For example, the approach ofFIG. 5can be carried out for this purpose as a preliminary check before the check according toFIG. 4.

It is also possible to perform the check ofFIG. 5in several stages, for example, in other words, to define a number of nested sections, and to output a more intensive warning, the further the person15progresses.

Furthermore, according to the flowchart inFIG. 6it is possible for the evaluation processor12to check in steps S41and S42whether it can identify the detected person15, whether, in other words, it can detect for example in step S41that the detected person15is a first, known person P1(“that is Mr. Müller”), or in step S42can detect that the detected person15is a second, known person P2(“that is Mrs. Braun”). This approach can of course also be expanded to more than two people. In this case the alarm condition can be met if the evaluation processor12cannot identify the detected person15. In this case the evaluation processor12could detect during the course of the evaluation of step S3that a person15is present, but not who the person15is.

The identification of the person can be configured as required. In particular, appropriate methods of facial recognition are generally known to persons skilled in the art. Alternatively or additionally, the stature of the person15can also be evaluated.

In the case of simultaneous detection of a number of individuals15, the embodiment ofFIG. 6can be configured such that the alarm condition is regarded as met, and the evaluation processor12cannot identify one of the individuals15. In the case of detection of a plurality of individuals15, the alarm condition is preferably only regarded as met, however, if the evaluation processor12cannot identify any of the detected individuals15. The approach ofFIG. 6can also be combined, as required—be it as an alternative, be it as an additional condition—with the approach ofFIG. 4,FIG. 5orFIGS. 4 and 5.

As a rule, the alarm condition is static from the perspective of the evaluation processor12. It is therefore specified to the processor12from outside and is not modified by the evaluation processor12. It is, however, possible for the evaluation processor12to be self-learning insofar as it can independently learn “non-critical” situations. This will be illustrated in more detail below in connection withFIG. 7.

FIG. 7starts fromFIG. 3. Reference will therefore be made to the statements above relating toFIG. 3(and also the embodiments according toFIGS. 4 to 6. In addition there is a step S51, however. Step S51is subordinate to step S11. It is therefore carried out if the termination command T is specified to the evaluation processor12in the alarm state Z2. In step S51the evaluation processor12modifies the alarm condition. The modification is such that the situation, detected during the course of evaluation of the group of images B, owing to which the alarm condition was regarded as having been met, is removed from the alarm condition. At any rate a lower weighting is associated with this situation in step S51. In the first case, the situation is immediately removed from the alarm condition. In the second case, the situation is weighted increasingly less, so, as a result, it is removed from the alarm condition after a number of iterations.

The present invention has many advantages. In particular, it is possible to almost completely prevent accidents, which can be attributed to accidental disregard of the safety regulations. The operational safety can be significantly increased.