JP2001155143A - Method for converting digital image pixel value and method for determining useful range of image pixel intensity value - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method which converts a value representing pixel intensity from an input dynamic range into an output dynamic range. SOLUTION: This method includes a process in which the lower limit of an appropriate part of a 1st range is decided, a process in which an intensity histogram representing a group of pixels having a prescribed intensity is prepared and a histogram that has been subjected to logarithmic conversion is prepared by converting the histogram, a process in which a threshold about the upper limit of values that have undergone logarithmic conversion is selected from the histogram that has been subjected to logarithmic conversion, a process in which a group of pixels having a value which has desired relation to the threshold and has undergone logarithmic conversion is selected, a process in which the upper limit of the appropriate part of the 1st range is determined on the basis of the selected group, a process in which the pixel value is converted into a conversion value over a 2nd range on the basis of the lower and upper limits, and a process in which an image related to the pixel value or information its supply source are transmitted between a 1st position and a 2nd position separated from the 1st position in order to perform a remote service.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

TECHNICAL FIELD The present invention relates generally to the field of medical diagnostic systems. More specifically, the present invention relates to techniques for converting digital image pixel values.

[0002]

2. Description of the Related Art Discrete imaging devices, such as digital x-ray imaging systems, use a detector that divides each region of an image into individual pixels. The array or matrix of pixels, when viewed as a whole image, defines a feature of interest, such as an internal anatomy of the subject located adjacent to the detector. To facilitate interpretation by a physician or technician,
The individual intensities of the pixels typically define image features by simulating the contrast and texture that can be obtained by conventional film-based x-ray or imaging systems.

[0003] To convert the detected pixel intensities into digital values suitable for display, the pixel intensity values are processed after acquisition by a detector. In the first stage, the detected pixel intensity is digitized as a value that varies over a predetermined dynamic range of the detector and acquisition circuit, for example, 12 to 14 bits. In an X-ray system, for example, these digital values represent the amount of X-rays received by each pixel during data acquisition. The pixel intensity values are then scaled to map to values in the dynamic range of the display. As part of this scaling, it is customary to perform a logarithmic transformation of the image pixel values to obtain an image simulating a conventional film-type image. In addition, the scaling process maps the dynamic range of the detector and acquisition circuitry to the dynamic range of the display. The latter range is
The range may be substantially different from the range of the upstream circuit, for example, about 8 bits to 10 bits.

While the logarithmic transformation of digitized pixel values is useful for representing images that can be understood by attending physicians and technicians, performing this transformation prior to dynamic range scaling is not an option. Can be a problem. For example, to analyze pixel intensity values,
Histograms are often used. However, processing histograms formed based on the transformed values may make it difficult to identify the upper and lower bounds of the appropriate portion of the detected data, making it difficult to scale the dynamic range. There is. The use of logarithmically transformed data prior to dynamic range scaling may also reduce the accuracy of individual pixels in the image matrix.

[0005] Therefore, there is a need for an improved method for processing discrete image data that facilitates using as much of each dynamic range of the acquisition and display circuits as possible. Specifically, in a computationally efficient manner, digital pixel values defining a discrete pixel image are shifted from a first dynamic range to a second
There is a need for improved methods for converting to a dynamic range of

[0006]

The solution to the above problem has not heretofore included significant remote capabilities. Specifically, there has been no attempt to provide a remote service for the above-mentioned medical diagnostic system using a communication network such as the Internet or a dedicated network. The advantages of remote services such as remote monitoring, remote system control, instant file access from remote locations, remote file storage and storage, remote resource collection, remote recording, remote diagnostics, remote high-speed computing, etc. solve the above problems. Was not conventionally used.

[0007] Therefore, there is a need for a medical diagnostic system that has the advantages of remote service and that can address the above problems. Specifically, there is a need for an improved method of processing discrete image data to provide remote services and functions such as remote diagnosis, transmission of image data over a network, storage of data at a remote location, and the like. Have been.

[0008]

The present invention, according to one embodiment, relates to a method for converting pixel values of a digital image from a first range to a second range, the method comprising:
(A) determining a lower limit of an appropriate portion of the first range; and (b) creating an intensity histogram representing a group of pixels having a predetermined intensity, transforming the histogram, and performing logarithmic conversion. Creating a histogram; (c)
Selecting a threshold value for the upper limit of the value after logarithmic conversion from the histogram after logarithmic conversion; and (d) a group of pixels having a value after logarithmic conversion having a desired relationship to the threshold value. (E) determining an upper limit value of the appropriate portion of the first range based on the selected population; and (f) based on the lower limit value and the upper limit value. Converting the pixel value into a conversion value over the second range; and (g) providing information about an image associated with the pixel value or a source thereof for a remote service to a first location and the first location. Transmitting to and from a second location remote from the first location.

[0009] Another embodiment of the present invention relates to a method of converting pixel values of a digital image from an input dynamic range to an output dynamic range, the method comprising: (a) generating a first histogram of the pixel values; Forming, (b) selecting a lower limit from the first histogram, and (c) forming a second histogram of the pixel values after logarithmic conversion of the pixel values by converting the first histogram. (D) selecting a group of pixels having a desired value after logarithmic transformation from the second histogram; and (e) selecting a group of pixels from the first histogram based on the selected group. Selecting an upper limit, and (f) based on the lower limit and the upper limit,
Converting the pixel values from the input range to a conversion value over the output range; and (g) providing information about an image associated with the pixel values or a source thereof to provide a remote service. Transmitting between a location and a second location remote from the first location.

Another embodiment of the present invention relates to a method for determining a useful range of image pixel intensity values in a digital pixel imaging system, the method comprising: (a) selecting a desired one of the pixels of the image; Determining the lower limit of the useful range by selecting the intensity value if the intensity value of a portion of the pixels is less than a particular intensity value; and (b) determining the intensity histogram and the intensity histogram. Creating a histogram after logarithmic conversion based on the histogram; and (c) selecting a threshold value for an upper limit based on the histogram after logarithmic conversion,
(D) selecting a group of pixels having a logarithmically transformed value having a desired relationship to the threshold; and (e) determining an upper limit of the useful range based on the selected group. And (g) transferring information about the imaging system or the image associated with the pixel values between a first location and a second location away from the first location to provide a remote service. And transmitting the data.

[0011] The basic features and advantages of the invention will be apparent to one skilled in the art from the figures and description, and from the claims.

A preferred embodiment will be described below with reference to the accompanying drawings. In the drawings, similar components are denoted by the same reference numerals.

[0013]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Referring now to FIG. 1, FIG. 1 shows an imaging system 10 illustrated in the form of an X-ray system. Note, however, that the techniques disclosed herein are not limited to use in such x-ray systems, but can be applied to other types of digital image processing modalities. I want to be. The imaging system 10 includes an X-ray source 12, which is configured to emit a stream of X-rays 14. When you want to take an image,
An object such as 6 is placed between the X-ray source 12 and the image acquisition unit 18. The image acquisition unit 18 includes a detector 20 and an intensity encoding circuit 22. X
Some of the X-rays emitted by the source 12 pass through the human body and enter the detector 20.

The detector 20 has a structure in which a surface for receiving X-rays is divided into discrete pixels or a matrix 24 of pixels. Detector 20 outputs a stream of data signals representing the intensity of the radiation received at each of the discrete pixel locations. Intensity encoding circuit 22 receives the data signal from detector 20 and encodes the intensity levels into a data stream. In this data stream,
An intensity level or intensity value for each pixel is assigned to a digital value over a predetermined dynamic range. For example, the intensity encoding circuit 22 may digitize the intensity values over a dynamic range of 12 to 14 bits per pixel,
This allows each pixel to be assigned 2 ¹² to 2 ¹⁴ different digital intensity values.

The signal receiving unit 18 then transmits these encoded values to the image processing unit 26 for further adjustment. Image processing unit 26 includes circuitry configured to process the digitized values and provide output data that can be displayed in a form that is understandable to a treating physician or technician. In the configuration illustrated in FIG. 1, the image processing unit 26 includes a decoding (decoding) circuit 28, a correction circuit 30, a value conversion circuit 32, and a signal processing circuit 34. Decoding circuit 28 receives the digital value from intensity encoding circuit 22 and partially decodes the information, such as by placing the pixel values in a desired order or sequence, as will be appreciated by those skilled in the art. The decoding circuit 28 then transmits the decoded value to a correction circuit 32, which calculates a digital intensity value that is directly proportional to the amount of X-rays received at each pixel location of the detector 20 during the acquisition process. Correction such as generation is performed on these values. As will be appreciated by those skilled in the art, correction circuit 30 may apply various corrections to these values, such as normalizing the decoded values to produce an optimal and consistent representation of the image acquired by the system. This can compensate for factors such as patient physique, tissue or structure composition of the human body, and X-ray dose.

Next, the corrected digital intensity value is
The value is sent to the value conversion circuit 32. The value conversion circuit 32 converts the digital intensity value from the range output by the intensity encoding circuit 22 to a range suitable for display as described below. These converted values are then further processed by the signal processing circuit 34. The signal processing circuitry 34 enhances structural details and textures.
Can be performed. Next, the signal processing circuit 34 outputs the output value of the digital image to the display / output device 36. Display / output device 36
Typically includes a monitor or printer capable of producing a discrete pixel image 38 representing a feature of interest inside the human body 16.

The value conversion circuit 32 includes a signal receiving unit 18
To account for the dynamic range difference between the value output by the control unit and the value required by the display / output device. For example, the pixel intensity values output by unit 18 may have a dynamic range of 12 to 14 bits per pixel, whereas the display /
The input range of output device 36 may be smaller, such as on the order of 8 to 10 bits per pixel. Both the acquisition circuit and the display circuit
In order to make the best use of the range, the value conversion circuit 32 analyzes the useful part of the dynamic range of the digitized value of the input and, based on this useful part, converts the digital value of the input. The converted values are converted to the dynamic range required by the display / output device 36.

It should be noted that the specific functional circuits, including the correction circuit 30 and the value conversion circuit 32 shown in FIG. 1, may be embodied in a general purpose or special purpose microprocessor or computer with appropriate code. . Further, the microprocessor or computer may be used to perform other functions or signal processing operations than those described herein.

FIG. 2 illustrates the control logic performed by the value conversion circuit 32, that is, the useful portion of the input digitized image pixel values and the conversion of these values to the dynamic range of the downstream circuit. 4 illustrates steps in typical control logic when converting or scaling. As shown in FIG. 2, when the value conversion circuit 32 receives a digital signal representing pixel intensity, a histogram h (x) is created to determine a pixel population having individual intensity values over the entire input dynamic range. . A schematic diagram of this type of histogram is illustrated in FIG.

As shown in FIG. 3, the histogram 52 is
It can be represented graphically by representing the intensity values 54 along the horizontal axis and plotting the number 56 of pixel populations for each intensity value along the vertical axis. The resulting graph forms a bar 58, which defines the distribution curve 60 in a stepwise manner. Each bar 5
8 has a width W, defining the entire dynamic range across the horizontal axis between a digital value corresponding to zero bits and a maximum value corresponding to 2 ⁱ -1 bits.
Here, “i” represents the number of bits in the input dynamic range. Also note that the sum of the population numbers for all of the intensity values is equal to the total population of pixels considered in the image.

For some images, the pixels have intensities over most of the valid input range (0-2 ⁱ -1), but the value conversion circuit 32 analyzes the input values and determines if the values are present. Determine the useful part of the dynamic range that exists. Thus, even if a smaller portion of the input dynamic range is used due to variations in the acquisition process, the converted value still provides the same amount of information available from the input value.

In the first step of this processing, step 4 in FIG.
As shown at 2, the value conversion circuit 32 determines the lower limit L of the useful range. This step is shown in the graph of FIG. In FIG. 3, reference numeral 62 shows an example of the lower limit L determined by referring to the histogram 52.
The lower limit is selected by locating the intensity value when the desired percentage of the total pixel population is below a certain intensity value along the horizontal axis. That is, starting with a zero intensity value, the number of pixels 56 on the bar 58 is integrated for each intensity value until the desired pixel population percentage is obtained. Once the above percentage is reached, a lower limit is set on the next higher intensity value.
In general, lower limits corresponding to 0.5% to 1% of the total pixel population have been found to give good results.

Referring back to FIG. 2, once the lower limit L is selected, a logarithmically transformed histogram h (f (x)) defined as g (x) is calculated as shown in step 44. . A histogram 64 after a typical logarithmic transformation is illustrated in FIG. The histogram after logarithmic transformation can be formed from the following equation.

H (f (x)) = xh (x) Here, the values of x and h (x) are based on the values of the pixel intensity histogram 52 of FIG. The histogram after logarithmic transformation can also be smoothed by using a low-pass filter technique, for example, by locally averaging the number of groups for each intensity value with the number of groups immediately before and immediately after. Such filtering helps smooth out any irregularities that may occur in the histogram profile.

Histogram g (x) after logarithmic transformation
Is established, the threshold value T is set as shown in step 46 of FIG.
To determine. Referring to FIG. 4 again, the threshold value T is determined from the histogram 64 after the logarithmic conversion. This is because, in FIG. 4, g at the position where the lower limit L indicated by the reference numeral 62 intersects the histogram after logarithmic conversion indicated by the intersection 68
This is performed by checking the value 66 of (x). Next, the histogram 64 is scanned starting from the value x = L to find the second intersection 70 where the value g (x) of the histogram is smaller than the threshold value T. The value of this intersection is
Form the basis for establishing an upper bound on the useful portion of the input dynamic range.

However, before determining the upper limit value, it is preferable to perform a confirmation comparison to determine whether a sufficient portion of the dynamic range has been selected by using the threshold value T. Specifically, the selected value 72
By comparing the value with a multiple of the lower limit, it was found that an appropriate test for the width of the dynamic range can be performed.
For example, if the selected value 72 is determined to be less than 2L, then the algorithm may include
ous), and a different threshold T
Can be required. In such a case, the threshold is reset to a smaller value, such as 0.8T, and the above procedure is performed using this reduced threshold to select a value 72 further along the histogram 64. .

Next, as shown in step 48 of FIG.
2, an upper limit H of a useful portion of the input dynamic range is determined. The value of H is set to a multiple of the value 72 determined as described above. Note that this multiple need not be an integer multiple and will generally be different for different types of modalities and subjects. For example, in a digital X-ray imaging system, a multiple of the value 72 used to set the upper limit H is:
It depends on the need to see the skin-air interface, lung interstitium or other details. For example, in radiography of the rib cage,
A magnification of 1.5 gives good results over the entire range of the image.

With the lower and upper bounds of the useful portion of the input dynamic range determined in this way, value conversion circuit 32 then converts the pixel values from the input range to the output range, as shown in step 50 of FIG. Scale to In a preferred approach, this transformation is performed according to the following relation:

Output = (2 ^b -1)-[(2 ^b -ε) ｛log (Input) / L｝
/ {Log (H / L)}] where the value "Output" is the scaled output value for each pixel, the value "Input" is the corresponding input value for this pixel, and b is the output Is the number of bits in the dynamic range, ε is a small number (less than 1.0, typically 0.5) used to ensure that the output value does not go below zero, and L
And H are a lower limit and an upper limit, respectively. Angle brackets represent operations that determine the largest integer value that is less than or equal to the amount of the real value enclosed by it. The transformation described by this equation inverts the height of the pixel values, so that pixels receiving low input values have higher output values (thereby inverting the brightness of the pixels in the resulting image). Note that This transformation is suitable, for example, in images such as radiographs of the rib cage. However, as will be appreciated by those skilled in the art, other transformations that do not invert the magnitude of the value may be appropriate in other applications.

It has been found that the above method can convert an input value into an output value in an efficient manner. Furthermore,
This procedure can be easily adapted to various imaging modalities and can be adapted to a wide variety of input and output circuits with substantially different dynamic ranges. Finally, the method automatically addresses the dynamic range bandwidth variation actually utilized, even with a single imaging system or with a particular image created for a particular subject. Provide more consistent and comparable images, thus facilitating image interpretation and analysis.

Referring now to FIG. 5, FIG. 5 illustrates a service system 1010 for providing remote service to a plurality of medical diagnostic systems 1012, including a system such as the imaging system 10 described with respect to FIG. .
In the embodiment shown in FIG. 5, a plurality of medical diagnostic systems include:
Included is a magnetic resonance imaging (MRI) system 1014, a computed tomography (CT) system 1016, and an ultrasound imaging system 1018. These diagnostic systems may be located at a single location or facility, such as medical facility 1020, or may be remote from others, as shown by ultrasound system 1018. The diagnostic system receives service from centralized service facility 1022. Further, multiple field service units 1024 may be coupled to the service system for transmitting service requests, verifying service status, transmitting service data, etc., as described in more detail below.

In the embodiment of FIG. 5, several different system modalities are provided for remote service by the service facility. By way of example and not limitation:
Remote services include remote monitoring, remote system control, instant file access from remote locations, remote file storage and storage, remote resource collection, remote recording, and remote high-speed computing. Remote services are offered for a particular modality, depending on the capabilities of the service facility, the type of diagnostic system subscribing to the service facility, and other factors. However, in general, the technology applies to a wide variety of medical diagnostic system modalities, including, for example,
It is particularly suitable for providing remote services for MRI systems, CT systems, ultrasound systems, positron emission tomography (PET) systems, nuclear medicine systems, and the like. Further, systems of various modalities serving in accordance with the present technology may be of different types, manufactures and models.

Various components or subsystems are included, depending on the modality of the system. MRI system 1
The 014 typically includes a scanner, control and control detection circuitry, a system controller, and an operator station. The MRI system 1014 includes a uniform platform for interactively exchanging service requests, messages and data with the service facility 1022 as described in more detail below. The MRI system 1014 is coupled to the communication module 1032,
The communication module may be included in the MRI system 1014 in a single or separate physical package. In a typical system, system 1014 includes additional components, such as a printer or photographic system for creating reconstructed images based on data collected from the scanner.

Similarly, CT system 1016 typically includes a scanner, a signal acquisition device, and a system controller. The scanner detects the portion of the X-ray that has passed through the object of interest. The control device includes a circuit that commands the operation of the scanner, and a circuit that reconstructs image data based on the acquired control. CT system 10
16 is coupled to a communication model 1048 for sending and receiving data for remote services. Furthermore, MRI
Like system 1014, CT system 1016
Generally, it includes a printer or similar device for outputting a reconstructed image based on data collected by the scanner.

The ultrasound system 1018 typically includes a scanner, a signal processor, and a system controller. The ultrasound system 1018 is coupled to a communication module 1062 for transmitting service requests, messages and data between the ultrasound system 1018 and the service facility 1022.

Although the term “scanner” for a diagnostic device is generally used herein, the term is not limited to image data acquisition, and generally includes medical diagnostic data acquisition devices, as well as medical devices. It should be understood that this includes image storage communication and retrieval systems, image management systems, facility or laboratory management systems, vision systems, etc. in the field of diagnostics.

For example, the MRI system 10 shown in FIG.
If two or more medical diagnostic systems are provided at one facility or location, as shown as 14 and CT system 1016, these systems may be managed as if they were within the hospital or clinic's radiology department. Station 107
Can be tied to zero. Management station 1070
May be directly coupled to various diagnostic systems. The management system may include a computer workstation or personal computer coupled to the system controller in an intranet configuration, in a file sharing configuration, in a customer / server configuration, or in any other manner. Further, management station 1070 typically includes
A monitor 1074 is included for visualizing system operational parameters, analyzing system availability, and exchanging service requests and data between facility 1020 and service facility 1022. Input devices such as a standard computer keyboard 1076 and mouse 1078 may be provided to form a user interface.

Note that, as an alternative, the components of the management system or other diagnostic system may be stand-alone, ie, not directly coupled to the diagnostic system. In such a case, some or all of the service platform and service functions described herein are provided on a management system. Similarly, depending on the application, the diagnostic system may comprise a stand-alone or networked image storage communication and retrieval system, or a vision station with some or all of the features described herein.

The communication module described above, along with the workstation 1072 and the field service unit 1024, may be coupled to the service facility 1022 via a remote access network 1080. A suitable network connection can be used for this purpose. Presently preferred network configurations include proprietary or dedicated networks and open networks such as the Internet. The data may be transmitted between the diagnostic system, the field service unit, and the remote service facility in any suitable format, such as the Internet Protocol (I
P), Transmission Control Protocol (TCP) or other known protocols. Further, depending on the data, the hypertext markup language (HTM)
L) or may be transmitted or formatted via a markup language such as L) or other standard languages. The presently preferred interface structure and communication components are described in more detail below.

Within service facility 1022, messages, service requests, and data are received by communication components, generally designated by reference numeral 1082. Component 1
082 sends service data to a service central processing system (generally designated 1084 in FIG. 5). The processing system manages the reception, handling and transmission of service data. Generally, the processing system 10
84 may include one or more computers and dedicated hardware or software to process various service requests and send and receive service data as described in more detail below.

The service facility 1022 also includes a group of operator workstations 1086 that process service requests and provide offline and online services to the diagnostic system in response to the service requests. Staff can be deployed. Further, the processing system 1084 is a service facility 1
It may be coupled to a database system or other processing system at 022 or remote from the facility. Such databases and processing systems may include extensive database information about operating parameters, service history, etc., for both a particular subscribed scanner and an expanded population of diagnostic devices.

FIG. 6 is a block diagram showing the components of the above-described system in terms of functions. As shown in FIG. 6, a field service unit 1024 and a diagnostic system 1012 are coupled to the scanner facility 1022 via a network connection indicated generally by 1080. Within each diagnostic system 1012, a uniform service platform 1090 is provided.

The platform 1090 (which will be described in more detail below with particular reference to FIG. 7) configures service requests, sends and receives service data, establishes network connections, and provides diagnostic systems and service facilities. And hardware, firmware and software components adapted to manage the financial or subscriber configuration between them. In addition, the platform provides a uniform graphical user interface (GUI) in each diagnostic system, which facilitates the interactive operation of the physician and radiologist with the various diagnostic systems for service functions. Can be adapted. The platform allows the scanner designer to work directly with the individual scanner control circuitry and scanner storage to access the images, records and similar files necessary to perform the requested or subscribed services. Enable. If a management station 1070 is provided, a similar uniform platform is preferably loaded into the management station to facilitate direct communication between the management station and the service facility. In addition to the uniform service platform 1090, each diagnostic system is preferably provided with a separate communication module 1092, such as a facsimile transmission module, for sending and receiving facsimile messages between the scanner and the remote service facility.

Messages and data transmitted between the diagnostic system and the service facility traverse a security barrier or "firewall" contained within the processing system 1084, as described below. Firewalls prevent unauthorized access to service facilities, as is generally known in the art. A modem rack 1096 containing a series of modems receives incoming data and sends outgoing data through router 110. The router manages the transfer of data between the modem and the service center processing system 1084.

In FIG. 6, an operator workstation 1086 is coupled to the processing system, and a remote database or computer 1088 is also coupled to the processing system. In addition, at least one local service database 1102 is provided for validating license and contract configurations and storing service record files, log files, and the like. Further, one or more communication modules 1104 are coupled to the processing system 1084 for sending and receiving facsimile transmissions between the service facility and the diagnostic system or field service unit.

FIG. 7 illustrates the various functional components that make up the uniform service platform 1090 within each diagnostic system 1012. As shown in FIG. 7, the uniform platform includes a device connection module 1106 as well as a network connection module 1108. Network connection module 110
8 accesses the main web page 1110, which, as previously described, is displayed on the monitor of the diagnostic system for the HT displayed for the system user.
It is preferably a page in a markup language such as an ML page. The main web page 1110 allows the user to set a review request, such as via an on-screen icon,
It is preferable to be accessible from a normal operation page where the user can view the examination result. Via the main web page 1110, a series of additional web pages 111
2 are accessible. Such a web page can configure and send a remote service request to a remote service facility and facilitate the exchange of other messages, reports, software, protocols, etc., as described in more detail below. .

As used herein, the term "page" includes a user interface screen or similar configuration that can be observed by a user of the diagnostic system, such as a screen that provides a graphical or textual representation of data, reports, and the like. Note that Further, such pages are defined by a markup or programming language such as java, perl, javascript or any other suitable language.

The network connection module 1108
Licensing module 1114 for verifying the status of a license, fee or contract application
Is joined to. The term "subscribe (subsc
It should be understood that "ription" includes various arrangements for the provision of services, information, software, etc., with or without payment, ie contractual, commercial or other arrangements. Further, special arrangements governed by the system described below may include several different types of applications, including, for example, deadline arrangements, one-time charge arrangements, so-called "pay-as-you-go" arrangements, and the like. .

The license module 1114 is coupled to the modality interface tool 1118 and one or more adapter utilities for communicating browsers, servers and communication components. In a presently preferred configuration, such an interface tool is provided for exchanging data between the system scanner and the service platform. For example, the modality interface tool 1118 forms a modality specific application, as well as configuration templates, graphical user
Applet or servlet for forming interface (GUI) custom code etc.
May be included. Adapter 1116 may operate interactively with such components, or modality controller 1 coupled to modality specific component 1122.
120 may operate directly interactively.

The modality controller 1120 and the modality specific component 1122 typically include a pre-configured processor or computer for performing the review, and image data files, log files, error files, etc. Includes memory for storage. Adapter 1116 communicates with such circuitry to convert between stored data and a desired protocol, such as Hypertext Transfer Protocol (HTTP) and DICOM.
(That is, medical image data display standard). In addition, the transfer of files and data as described below may be performed via any suitable protocol, such as File Transfer Protocol (FTP) or other network protocols.

In the illustrated embodiment, the device connection module 1
106 includes several components for exchanging data between the diagnostic system and a remote service facility. Specifically, the connection service module 11
24 is provided for communicating with the network connection module 1108. A point-to-point protocol (PPP) module 1126 is also provided for transmitting Internet Protocol (IP) packets over a telecommunications connection. Finally, a modem 1128 is provided for transmitting and receiving data between the diagnostic system and the remote service facility. As will be apparent to those skilled in the art, various other network protocols and components can be used in the device connection module 1106 to facilitate such data exchange.

The network connection module 1108
Preferably, it includes a server 1130 and a browser 1132. The server 1130 facilitates the exchange of data between the diagnostic system and the service facility and allows a series of web pages 1110 to be viewed via the browser 1132. In the currently preferred embodiment, server 1130 and browser 1132 support HTTP applications, and browsers support Java applications. Of course, other servers and browsers or software packages can be used to exchange data, service requests, messages and software between the diagnostic system and the operator and remote service facility. Finally, the direct network connection 1134 is connected to the server 1130 and the management station 1070 in the medical facility.
(See FIGS. 5 and 6).

In this embodiment, the components that make up the network connection module can be configured through an application stored as part of the uniform platform. Specifically, a Java application licensed to a service technician allows the technician to configure the device connection module of the diagnostic system to connect to a service facility.

FIG. 8 illustrates typical functional components for service facility 1022. As noted above, service facility 1022 includes a modem rack 1096, which has a plurality of modems 1098 coupled to a router 1100 that coordinates data communication with the service facility. HTTP service server 1
094 is a transaction (transac
and receive direction. The server 1094 is coupled to other components of the facility via a firewall 1138 for system security. An operator workstation 1086 is coupled to the port manager for processing service requests and sending out messages and reports in response to such requests.

The service facility has an automatic service unit 1136 that automatically responds to certain service requests and performs operations such as sweeping subscribing diagnostic systems for operating parameter data as described below. Is also included. In a presently preferred embodiment, the automated service unit can operate independently of or in conjunction with the interactive service components that make up the processing system 1084. Here, the service facility communicates with the diagnostic system and with remote service units, such as systems including external Internet Service Providers (ISPs), Virtual Private Networks (VPNs), etc., and communicates data and messages. It should be noted that other networks or communication schemes may be provided to enable the exchange of

After the firewall 1138, the HTTP application server 1140 coordinates service request handling, message transmission, reporting, software forwarding, and the like. The HTTP server 1140 includes a service analysis server 114 configured to handle specific types of service requests, as described in more detail below.
Other servers such as 2 can be combined. In the illustrated embodiment, processing system 1084 also includes a license
Server 1144 and includes a license server 11
44 is coupled to the license database 1146 for storing, updating and verifying the status of diagnostic system service subscriptions. Alternatively, if desired, license server 1144 can be installed on firewall 1138.
May be placed outside the service facility to verify the status of the application before entering the service facility.

The handling of service requests, message transmission and reporting are further coordinated by a scheduler module 1148 coupled to the HTTP server 1140. The scheduler module 1148 includes, for example, a report server 1150, a message server 1152, and a software download server 1154.
Coordinate the activities of other servers that make up the processing system.
As will be appreciated by those skilled in the art, servers 1150, 115
2 and 1154 are coupled to a memory device (not shown) for storing data such as addresses, log files, messages and report files, application software, and the like. Specifically, as shown in FIG. 8, the software server 1154 communicates with the storage device 11 via one or more data channels to accommodate software packages.
56 and the software package is
It can be sent directly to the diagnostic system, accessed by the diagnostic system, or supplied by pay-per-use or purchase. Messages and reports 1152 and 1150 are in communication module 1
Coupled along 104 to the dispatch processing module 1158, the dispatch processing module 1158 is configured to receive the outgoing message, ensure proper connection with the diagnostic system, and coordinate the transmission of the message. I have.

In the presently preferred embodiment, the functional circuitry described above can be implemented as hardware, firmware, or software on a computer platform. For example, the functional circuit of a diagnostic system
Appropriate code can be programmed into a personal computer or workstation that is incorporated entirely into or attached to the scanner of the system. The functional circuitry of the service facility may include an additional personal computer or workstation in addition to the main frame computer on which one or more servers, schedulers, etc. are configured. Finally, the field service unit can comprise a personal or laptop computer of any suitable processor platform. It should be noted here that the aforementioned functional circuits can be modified in various ways to perform the functions described herein. Generally speaking, the functional circuitry facilitates the exchange of remote service data between the diagnostic system and a remote service facility, preferably to provide for periodic updates of service activity to the diagnostic system. In an interactive manner.

As mentioned previously, both the diagnostic system and the field service unit preferably communicate between the various diagnostic system modalities and the remote service facility via an interactive user-observable page. make it easier.
Representative pages include the ability to provide interactive information, form service requests, select and transmit computer software with messages and reports.
The page includes the interaction and use of remote services such as remote monitoring, remote system control, instant file access from remote locations, remote file storage and storage, remote resource collection, remote recording, remote diagnostics, remote high speed computing, etc. make it easier.

The user can access a particular document described in the text area of the page by selecting all or part of the text describing the document. In the currently preferred embodiment,
The accessed document can be stored in a local memory device within the diagnostic system, or by selection of text,
A uniform resource locator (URL) for accessing a remote computer or server via a network connection can be loaded.

The service system (FIG. 5) has the advantage of providing remote services, such as software upgrades, remote diagnostics, inspection, remote image storage, and improved processing methods. Processing of the image data can be performed to provide a variety of provisions, including enabling remote visualization, remote computation or analysis of images, and high-speed transmission of images.

While the embodiments shown in the drawings and described above are presently preferred, it should be understood that these embodiments are provided by way of example. Other embodiments include providing improved network services with the networks described above. The invention is not limited to any particular embodiment, but extends to various modifications, combinations and permutations that fall within the scope and spirit of the following claims.

[Brief description of the drawings]

FIG. 1 is a block diagram of an X-ray imaging system that includes circuitry for converting input values for individual pixels of an image into output values for display.

FIG. 2 is a flow diagram illustrating exemplary control logic for converting or scaling digitized pixel values over a first dynamic range to values over a second dynamic range for display.

FIG. 3 is an exemplary histogram of pixels having predetermined intensity values for an image detected by the system of FIG. 1 according to the logic of FIG. 2;

FIG. 4 is an exemplary histogram of transformed pixel values created based on the histogram of FIG. 3 according to the logic of FIG. 2;

FIG. 5 is a diagram illustrating a series of diagnostic systems coupled to a service facility via a network connection for remote service and data exchange between the diagnostic system and the service facility.

FIG. 6 is a block diagram showing specific functional components of a diagnostic system and a service facility of the system shown in FIG. 5;

FIG. 7 is a block diagram of certain functional components within a diagnostic system of the type shown in FIGS. 5 and 6 for facilitating interactive remote service of the diagnostic system.

FIG. 8 is a diagram showing a service facility shown in FIGS. 5 and 6;
FIG. 2 is a block diagram of certain functional components for providing interactive remote service to multiple medical diagnostic systems.

 ────────────────────────────────────────────────── ─── Continued on the front page F term (reference) 5B057 AA07 BA03 CA08 CA12 CA16 CB08 CB12 CB16 CE11 DA04 DB02 DB09 5C077 LL01 LL19 NN03 PP05 PP15 PP16 PQ08 PQ19

Claims (22)

[Claims] 1. A method for converting pixel values of a digital image from a first range to a second range, comprising: (a) determining a lower limit of an appropriate portion of the first range; (C) generating an intensity histogram representing a group of pixels having a predetermined intensity, converting the histogram to generate a histogram after logarithmic conversion, and (c) calculating a value of the value after logarithmic conversion from the histogram after logarithmic conversion. Selecting a threshold for the upper limit; (d) selecting a population of pixels having a logarithmic transformed value having a desired relationship to the threshold; and (e) the selected population. Determining an upper limit of the appropriate portion of the first range based on: (f) converting the pixel value to a transformed value over the second range based on the lower limit and the upper limit. Convert (G) transferring information about the image associated with the pixel value or its source between a first location and a second location away from the first location to provide a remote service. Transmitting. 2. The method according to claim 1, wherein at least one of the steps (a) to (f) is performed at the second position.
The method described in. 3. The method according to claim 1, wherein the population selected in the step (d) is a population having a logarithmically transformed value smaller than the threshold. 4. The method of claim 1, wherein the lower limit is determined based on a population of pixels selected in the intensity histogram. 5. The method according to claim 3, wherein the upper limit is determined based on the histogram after the logarithmic transformation and the population selected in step (d). 6. The method according to claim 1, wherein the threshold value corresponds to a desired value after logarithmic transformation. 7. The method of claim 6, wherein the population selected in step (d) is selected by comparing the threshold to a log transformed value in the log transformed histogram. 8. The method according to claim 1, further comprising: comparing the population selected in the step (d) with a desired population size; and resetting the threshold based on the comparison. The method described in. 9. A method for converting pixel values of a digital image from an input dynamic range to an output dynamic range, comprising: (a) forming a first histogram of the pixel values; and (b) the first histogram. Selecting a lower limit from the histogram; (c) forming a second histogram for the logarithmically transformed values of the pixel values by transforming the first histogram; (d) the second histogram (E) selecting an upper limit value from the first histogram based on the selected population; and (f) selecting an upper limit value from the first histogram based on the selected population. Converting the pixel value from the input range to a converted value over the output range based on a lower limit and an upper limit; Transmitting information about the image associated with the pixel value or its source between a first location and a second location remote from the first location to perform the image processing. The above method. 10. The method of claim 9, wherein at least one of steps (a) to (f) is performed at the second location. 11. The method according to claim 9, wherein the population is selected by referring to a desired log-transformed threshold in the step (d). 12. The method according to claim 1, further comprising the step of comparing the selected output range with a desired output range, and correcting the desired logarithmic transformed threshold based on the comparison.
2. The method according to 1. 13. The method of claim 12, wherein the desired output range is determined based on the lower limit. 14. The method of claim 9, wherein the lower limit is selected based on a particular value, wherein the particular value is such that a desired portion of the pixels has a smaller value. the method of. 15. A method for determining a useful range of image pixel intensity values in a digital pixel imaging system, comprising: (a) determining that the intensity values of a desired portion of the pixels of the image are greater than a particular intensity value; Determining the lower limit of the useful range by selecting the intensity value if the intensity value is also smaller; and (b) generating an intensity histogram and a histogram after logarithmic transformation based on the intensity histogram. (C) selecting a threshold value for an upper limit based on the histogram after the logarithmic conversion; and (d) selecting a group of pixels having a logarithmically converted value having a desired relationship with the threshold value. (E) determining an upper limit of the useful range based on the selected population; and (g) performing a remote service. The imaging
Transmitting information about a system or an image or source thereof associated with the pixel values between a first location and a second location remote from the first location. The above method. 16. The method of claim 15, wherein at least one of steps (a) to (f) is performed at said second location. 17. The method according to claim 15, wherein the population selected in the step (d) is a population having a logarithmically transformed value smaller than the threshold. 18. The method of claim 15, wherein the lower limit is determined based on a population of pixels selected in the intensity histogram. 19. The method according to claim 18, wherein the upper limit value is determined based on the histogram after the logarithmic transformation and the population selected in the step (d). 20. The method according to claim 15, wherein the threshold value corresponds to a desired value after logarithmic transformation. 21. The method of claim 20, wherein the population selected in step (d) is selected by comparing the threshold with a log transformed value in the log transformed histogram. 22. comparing the population selected in step (d) with a desired population size;
Resetting the threshold based on the comparison.