Patent Application
20070118550
This invention relates to a method and apparatus for building a multidiscipline and multi-media personal medical image library and refers particularly, though not exclusively, to such a method and apparatus using medical images of different formats and sources.
Throughout this specification the following abbreviations and acronyms shall have the following meanings:
Medical (e.g. radiology, pathology, endoscopy, and so forth) images are important building blocks for clinical support, teaching and research. In the digital environment, medical images may be organized and cross-referenced in a powerful and interactive fashion. As more clinicians use digitized images, a personal medical image library Will become a valuable tool for on-demand learning, research, and exchange of data. However, a solution does not yet exist to build such a library that can collect and store medical images of various disciplines and formats. Medical Imaging Resource Center (MIRC), which was developed in 2001, is a standardized platform for exchanging image data.
Many clinicians from all kinds of disciplines have their own hardcopy medical image collections for archive, teaching and research. But there is no open standard for them to organize and share them. Recently, the Radiological Society of North America has defined standards for Medical Image Resource Center. MIRC has the potential to be a worldwide set of standards defining teaching file and research data sets in the same fashion as DICOM has become the de facto standard for PACS.
There are no known systems for obtaining medical images and other information from various sources to compose radiological teaching files and research datasets in a personal file library able to be shared with other libraries using the MIRC protocol.
In accordance with a preferred aspect of the invention there is provided a method for retrieving medical images from various sources and in different formats, to enable the creation of teaching files and research datasets, for the building of a personal medical image library, the method comprising:
The method may further include a searching mechanism for searching the teaching files and research datasets.
The medical images may be from at least one discipline selected from: radiology, nuclear medicine, dermatology, pathology, ophthalmology, cardiology, neurology, endoscopy, angiography, biomedicine, ECG, EEG, and EMG.
Preferably, the method is in accordance with MIRC schema.
The method may further include anonymizing patient sensitive information, the patient sensitive information being able to be revealed to a generator of the teaching files and research datasets. Preferably, the patient sensitive information is not revealed publicly. The anonymization process may include the replacing of each item of the sensitive information with an anonymization code. The anonymization code may include a prefix, a randomly generated number, and a type. The prefix may be a short string of characters representing the generator of the sensitive information; and the type may represent the nature of the sensitive information.
A check may first be performed to determine if the item of sensitive information has previously been anonymized and the anonymization code previously generated; and, if yes, retrieving and using the previously generated anonymization code.
The sensitive information may include one or more of: patient's name, patient ID, other patient's names, other patient IDs, patient's birth name, patient's address, patient's telephone numbers, patient's mother's birth name, region of residence, country of residence, military rank, branch of service, patient comments, additional patient history, referring physician's name, referring physician's address, referring physician's telephone numbers, and all other person names.
In step (c), ACR codes may be entered as a result of system prompts. The ACR codes may be used for the at least one index of the teaching files.
Indexing may be by at least one of: title, abstract,- keywords, authors, affiliations, contacts, patient information, radiological codes, image format, image compression status, image modality, anatomic location, and ACR codes.
For internal searching, patient sensitive information may be revealed, and for external searching patient sensitive information may be anonymized.
In accordance with a second aspect of the invention there is provided apparatus for retrieving medical images from various sources and in various formats for creating at least one teaching file and research dataset; the apparatus including a database, an image retrieval interface able to retrieve medical images from various sources and in different formats, an MIRC server, a server, and a graphic user interface for operation on a users machine.
The database is preferably a relational database for storage of all required information, including: database tables; database indexes; database scripts; and pointers to the medical images, teaching files and research datasets.
The server preferably serves requests received from a user via the graphic user interface on a users machine; the graphic user interface being for providing access functions and file editing functions.
The image server may include at least one of: a two dimensional image loader, a three dimensional image loader, a multi-media loader, and a telemetry loader.
The two-dimensional image loader is for retrieving two-dimensional still images, the three-dimensional image loader is for retrieving three-dimensional still images; the multi-media loader is for retrieving multi-media files; and the telemetry loader is for retrieving telemetry data.
The graphic user interface may include a PMIL client as a user interface able to run in a web browser or as a stand alone application on a user's machine, and provides MIRC editing functions.
The server may include an MIRC storage for providing an MIRC file storage service for the database and for the user's machine. The MIRC server may further include an MIRC query to provide queries as defined by the MIRC scheme.
The at least one teaching file may be in accordance with a Medical Imaging Resource Centre standard.
In a final aspect of the invention there is provided a computer useable medium comprising a computer program code that is configured to cause a processor to execute one or more functions to perform the method outlined above.
In order that the invention may be fully understood and readily put into practical effect there shall now be described by way of non-limitative example only preferred embodiments of the invention, the description being with reference to the accompanying illustrative drawings in which:
This system serves as a personal medical image library that stores and organizes medical images and metadata in a database, it can also be used to exchange image data in the global MIRC community.
As shown in
The database 1 is preferably a relational database. The database 1 stores all information for the system, including database tables, database indexes, and database scripts; and also stores the pointers to the physical files of the system.
The image retrieval interface 2 is able to retrieve images of various disciplines and formats. The MIRC server 3 provides MIRC compliant functions, including MIRC query and MIRC storage.
The Web server 4 services the various requests of the GUI, and the GUI 5 provides functions to access the system. GUI 5 also provides MIRC file editing functions.
A more detailed structure is illustrated in
The web server 4 includes a PMIL servlet 25 running in the web server 4 to serve requests from the GUI 5.
The GUI 5 includes a PMIL client 26 as the user interface. The PMIL client 26 can be run in a web browser or as a stand alone application.
The MIRC server 3 includes a MIRC storage 27 that provides MIRC teaching file storage service; and an MIRC query 28 provides queries as defined by the MIRC schema.
As shown in
Different departments of a hospital generate a large number of medical images for various diagnosis purposes. Most images are in digital format, and are stored in digital media. Some images are typical or atypical; they are particularly suitable teaching and research.
The first step of retrieving medical images (31) involves reading medical images stored in digital media. Various way of reading images are used including, but not limited to:
Different image formats may be supported including, but not limited to:
For all supported formats, the relevant application for dealing with the format is provided, and is fully integrated into the operating system. All images are kept in their original format once retrieved. For two-dimensional images, two additional JPEG images may be generated for ease of browsing using a web browser. These additional images may be of the same size as the thumbnail images. For other image formats, an additional thumbnail image may be generated.
When images are loaded from the open image dialogue, all supported images can be previewed in the dialogue, before they are actually loaded. In this way it is possible to load images of interest.
In step 32, after the images are loaded, then can be viewed in the image window and selected to add into teaching files and research datasets, and further stored in the database (1).
Since medical images are usually large in size, they need a large amount of disk space to store. The image storage may be spanned to multiple storage media. When the current storage media in use is approaching being filled, a storage media with sufficient free space is located and subsequently used.
Patient specific information retrieved from the clinical image archive is very sensitive and can only be referenced internally. It is not allowed to appear in teaching files and datasets, which may be published. Patient sensitive information can't be simply removed from the teaching files. Sometimes it is required to be able refer back to the actual patient. Therefore, patient sensitive information needs to be anonymized. There are two places where patient information may appear: in the database record and in DICOM files.
In the database record, the patient name and ID are stored. The process described below may be used to anonymize them.
The anonymization process has the format of:
<Prefix><Type>−<Number>
Where, prefix is usually a small number of letters. The letters may represent the creator of the anonymized information. Typically, the letters may be the acronym of the creating institute such as, for example, “BIL”.
Type specifies the nature of the anonymized information. Since patient name and ID are most frequently referenced, a “P” and a “D” may be used to represent them respectively. An “X” may be used to represent all other types of information. Further classification is also possible, for example, an “A” can be used to represent address information.
Number is a random number uniquely generated to distinguish the anonymized code from other codes.
For example, a code, “BILP-3388”, represents a patient name, is created by an organization named “BIL”.
As shown in
The system keeps the correspondence relationship between the-sensitive information and the anonymized code in the database. It may also provide a method to reveal the information before anonymization by looking up the database, but this method is preferably only used internally.
As shown in
Sensitive information may include, but is not limited to:
The following steps are then used:
By using this anonymization method, no patient-sensitive information is disclosed, but the generator can obtain the information.
As shown in
Author information and affiliation information may be retrieved automatically from the database 1 and then inserted into the teaching file database record.
A user interface 5 is provided to enter other necessary information such as copyright information, title, difficulty level, access permission, publishing date, reviewer, abstract, keywords, clinical findings, image findings, radiological codes, diagnosis, diagnosis groups, pathology of condition, imaging of condition, differential diagnosis, similar cases, quiz and references, and so forth. ACR coding system is used in the Teaching File and Research Dataset record. An ACR code has the following format:
<aaaa>. <pppp>
Where <aaaa>is the anatomy part, and <pppp>is the pathology part. They are digits from 0 to 9.
The ACR code is input (61) by user remembering and inputting the radiological codes or by the system guiding the user to input the ACR code step-by-step, or digit by digit. At each step, the system prompts the user with only the possible digits at the current position and the text of corresponding meanings. The first prompt (62) is for the anatomy code. After the entry or selection of the anatomy code (63), a query is raised to determine if there are sub-anatomy codes (64). If not (65), the next section is the pathology section (66). If yes, a further prompt is raised (67) and the relevant data is entered or selected (68). This may be repeated until the pathology section is entered (69) whereupon the system prompts for the pathology code (70). Upon the relevant pathological data being entered or selected (71) the system enquiries if there are more sub-pathology codes (72). If not, there are no more prompts (73) and the process ends (74). If yes, a prompt is raised (75) and the relevant data entered or selected (76). Steps 72, 75 and 76 may be repeated until other fields are selected (77), and the process ends (74).
Based on the database record generated in step 34 of
A significant image inserted into the teaching files has two forms: a thumbnail, and a full image. The thumbnail image may be in JPEG format, and the full image may be in its original format or JPEG format.
The case record and the XML file together with significant images (thumbnails and full images) may stored permanently in the database in step 36 for later access. Later access may be for indexing, searching and retrieving.
The teaching files and research datasets stored in the database 1 may be indexed in various categories for searching purposes in step 37. The index categories may include title, abstract, keywords, authors, affiliations, contacts, patient information, radiological codes, image format, image compression status, image modality, anatomic location, and so forth.
Internet based searching mechanisms are provided in step 38. There may be two types of searching mechanisms: internal searching and external searching. For internal searching, patient sensitive information is exposed, whereas for external searching, this information is anonymized as is described above.
Computer useable medium comprising a computer program code that is configured to cause a processor to execute one or more functions to perform a method for retrievirig medical images from various sources and in different formats, to enable the creation of teaching files and research datasets, for the building of a personal medical image library, the method comprising:
Whilst there has been described in the foregoing description preferred embodiments of the present invention, it will be understood by those skilled in the technology that many variations or modifications in details of one or more of: design, construction and operation, without departing from the present invention.
| Number | Date | Country | Kind |
|---|---|---|---|
| 200306928-3 | Nov 2003 | SG | national |
This invention is related to the earlier U.S. patent application Ser. No. 10/307,190 filed 28 Nov. 2002 entitled “A Method and Apparatus for Creating Medical Teaching Files From Image Archives”, the contents of which are hereby incorporated by reference (the “earlier patent application”).
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/SG04/00382 | 11/24/2004 | WO | 5/26/2006 |
