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WO2025111649A1 - Système de transfert de fichier médical - Google Patents

Système de transfert de fichier médical Download PDF

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Publication number
WO2025111649A1
WO2025111649A1 PCT/AU2024/051268 AU2024051268W WO2025111649A1 WO 2025111649 A1 WO2025111649 A1 WO 2025111649A1 AU 2024051268 W AU2024051268 W AU 2024051268W WO 2025111649 A1 WO2025111649 A1 WO 2025111649A1
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WO
WIPO (PCT)
Prior art keywords
image
image model
remote
session
local
Prior art date
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Pending
Application number
PCT/AU2024/051268
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English (en)
Inventor
Thomas William MORRELL
James Richard HILL
Martina MARIANO
Elliott Damian COOPER
André Marchezini ROCHA
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Singular Health Pty Ltd
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Singular Health Pty Ltd
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Publication date
Priority claimed from AU2023903836A external-priority patent/AU2023903836A0/en
Application filed by Singular Health Pty Ltd filed Critical Singular Health Pty Ltd
Publication of WO2025111649A1 publication Critical patent/WO2025111649A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/08—Volume rendering
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing

Definitions

  • Sharing of medical files, specifically image-based test results and related visual patient data, can be problematic.
  • producers of such medical image files and test results such as those produced via computed tomography (CT) scans, X-ray imaging, magnetic resonance imaging (MRI) scans, ultrasound, etc., to provide print-outs of scan images, or store imaging data on portable storage devices, such as CD-ROMS, flash drives, or similar electronic storage mediums, when the information is provided to a patient or transferred to another medical professional.
  • CT computed tomography
  • MRI magnetic resonance imaging
  • ultrasound etc.
  • portable storage devices such as CD-ROMS, flash drives, or similar electronic storage mediums
  • DICOM Digital Imaging and Communications in Medicine
  • 'the Internet generally refers to any suitable communications network and typically includes reference to a global system of interconnected computer networks that use the Internet protocol suite (TCP/IP) to link processing devices worldwide.
  • TCP/IP Internet protocol suite
  • Such a network includes a network of networks that may consist of private, public, academic, business, and government networks of local to global scope, linked by a broad array of electronic, wireless, and optical networking technologies.
  • reference herein to 'substantial real-time' is to be understood as meaning an instance of time that may include a delay typically resulting from processing, calculation and/or transmission times inherent in networked computer processing systems. These transmission and calculations times, albeit of generally small duration, do introduce some delay, i.e. typically less than a second or within milliseconds, but the user is provided with relevant visualisation information relatively quickly or within 'substantial real-time' .
  • reference herein to medical image files comprises broad and nonlimiting reference to image-based medical information, such as image data produced via computed tomography (CT) scans, X-ray imaging, magnetic resonance imaging (MRI) scans, positron emission tomography (PET) scans, ultrasound, and other medical imaging modalities, and includes the DICOM protocol. Additionally, the skilled addressee is to appreciate that such medical image files may also comprise non-image data, including medical records, patient details, etc.
  • CT computed tomography
  • MRI magnetic resonance imaging
  • PET positron emission tomography
  • a computer-implemented method for collaborative medical image file sharing comprising the steps of: receiving medical image files, via an acquisition and discrimination module (ADM) , said ADM configured to subject the image files to input quality control (IQC) according to a predetermined protocol and, i f IQC is success ful , to store said image files on a local database and assigned a unique patient identi bomb ; upon receipt of a request , via a locally-provided GUI , from a user providing such unique patient identi fier, creating a primary session where the image files are loaded into local non-transitory memory; voxelising the image files to produce a 3D re-constructed multi-planar image model within such primary session in the local non-transitory memory; enabling, via the locally-provided GUI , user interaction with said image model in the primary session to enable visualisation and annotation of the image model in substantial real-time ; capturing such user interaction in local non-
  • the step of receiving the medical image files comprises receiving said files selectable from a group consisting of local storage , a picture archiving and communication system ( PACS ) , Secure File Trans fer Protocol (SFTP ) , a Radiology Information System (RIS ) , and removable media .
  • PACS picture archiving and communication system
  • SFTP Secure File Trans fer Protocol
  • RIS Radiology Information System
  • the medical image files are selectable from a group consisting of DICOM files , MRI , CT , XR, MG and PET patient scan files .
  • the step of the ADM subj ecting the received image files to input quality control ( IQC ) according to a predetermined protocol comprises said ADM inspecting header information from DICOM images and comparing header tags between images for consistency .
  • the steps of receiving the medical image files with IQC, storing the image files on a local database assigned the unique patient identi bomb, enabling user interaction via the locally-provided GUI , creating the primary session, voxelising and capturing the sessional analysis information are performed on a local unitary computer system comprising the local database and local non-transitory memory, said local unitary computer system networked to a remote unitary computer system comprising the remote non-transitory memory .
  • the step of voxelising comprises sequentially processing the medical image files by assigning each image pixel a 3D coordinate to convert said images into a voxelised image data cube wherein each voxel is represented by an x, y and z axis value , said image data cube forming the 3D re-constructed multi-planar image model within the primary session .
  • the step of enabling user interaction via the locally-provided GUI with the image model in the primary session in substantial real-time comprises rendering the image model in 3D, enabling navigation of the image model (pan, zoom, rotate ) , enabling viewing the image model in di f ferent planes ( axial , sagittal , coronal ) , enabling manipulating the visualisation (planar intersection, density ad ustments ) , adding and/or editing annotations to the image model , capturing images of aspects of the image model , and/or measuring features of the image model .
  • the method includes the step of , upon receipt of the collaboration request , establishing a voice and/or video communication link between the local and remote computer systems .
  • the step of capturing the user interaction as sessional analysis information comprises capturing and transposing annotations , measurements and graphical markups made via the GUI on any 2D image plane to corresponding coordinates in the voxelised 3D image model .
  • the method comprises the step of overlaying the sessional analysis information onto the visualisation of the image model in substantial real-time for the primary session, and i f active , the secondary session .
  • the method includes the step of anonymising the visualisation of the image model and sessional analysis information prior to transmission to the secondary session in the remote non-transitory memory .
  • the method includes the step of , upon receipt of a collaboration request , enabling user interaction via the remote GUI with said image model in the primary session to enable visualisation and annotation of the image model by a remote user in substantial real-time .
  • the step of creating a secondary session in remote non-transitory memory comprises creating a plurality of distinct secondary sessions in respective remote non- transitory memories to enable collaboration between more than two users .
  • the method includes the step of uploading the image model and sessional analysis information from the local database to networked cloud storage.
  • the method includes the step of exchanging the image model and sessional analysis information with a picture archiving and communication system (PACS) .
  • PACS picture archiving and communication system
  • the method includes the step of subjecting the image model and/or sessional analysis information to artificial intelligence/machine learning (AI/ML) when uploaded to, or downloaded from, networked cloud storage.
  • AI/ML artificial intelligence/machine learning
  • a collaborative medical image file sharing system comprising : a host computer system comprising a processor, local non- transitory memory, a local database, a network interface and a local display; at least one guest computer system operatively networked with said host computer system via a communications network and comprising a processor, remote non-transitory memory, a display and a network interface; wherein the host computer system is configured to, via the processor executing software instructions: i.
  • ADM acquisition and discrimination module
  • IQC input quality control
  • the host computer system receives the image files selectable from a group consisting of local storage, a picture archiving and communication system (DAGS) , Secure File Transfer Protocol (SFTP) , a Radiology Information System (RIS) , and removable media.
  • DGS picture archiving and communication system
  • SFTP Secure File Transfer Protocol
  • RIS Radiology Information System
  • the medical image files are selectable from a group consisting of DICOM files, MRI, CT, XR, MG and PET patient scan files.
  • the host computer system processor enables user interaction via the locally-provided GUI with the image model in the primary session in substantial real-time by interactively rendering the image model in 3D on the display, enabling navigation of the image model (pan, zoom, rotate ) , enabling viewing the image model in di f ferent planes ( axial , sagittal , coronal ) , enabling manipulating the visualisation (planar intersection, density adj ustments ) , adding and/or editing annotations to the image model , capturing images of aspects of the image model , and/or measuring features of the image model .
  • the host computer system processor is configured, upon receipt of the collaboration request , to establish a voice and/or video communication link between the host and guest computer systems .
  • the host computer system processor is configured to capture the user interaction as sessional analysis information by capturing and transposing annotations , measurements and graphical markups made via the GUI on any 2D image plane to corresponding coordinates in the voxelised 3D image model .
  • the relevant computer system processor is configured to overlay the sessional analysis information onto the visualisation of the image model in substantial real-time for the primary session, and i f active , the secondary session .
  • the host computer system processor is configured to anonymise the visualisation of the image model and sessional analysis information prior to transmission to the secondary session in the remote non-transitory memory of the guest computer system .
  • the host computer system processor is configured, upon receipt of a collaboration request , to enable user interaction via the remote GUI with said image model in the primary session to enable visualisation and annotation of the image model by a remote user of the guest computer system in substantial real-time .
  • the host computer system processor is configured to create the secondary session in the remote non- transitory memory by creating a plurality of distinct secondary sessions in respective remote non-transitory memories of separate guest computer systems to enable collaboration between more than two users .
  • the host computer system processor is configured to upload the image model and sessional analysis information from the local database to networked cloud storage .
  • the host computer system processor is configured to exchange the image model and sessional analysis information with a picture archiving and communication system ( PACS ) .
  • PACS picture archiving and communication system
  • the host computer system processor is configured to subj ect the image model and/or sessional analysis information to arti ficial intelligence/machine learning (AI /ML ) when uploaded to , or downloaded from, networked cloud storage .
  • AI /ML arti ficial intelligence/machine learning
  • a medical image file trans fer system comprising : a host computer system comprising a processor, local non- transitory memory, a local database , a network interface and a local display; at least one remote server system operatively networked with said host computer system via a communications network and comprising a processor, remote non-transitory memory, a display and a network interface ; and at least one guest/remote receiver computer system operatively networked with said host computer system via a communications network and comprising a processor, remote non- transitory memory, a display and a network interface ; wherein the host computer system is configured to , via the processor executing software instructions : a .
  • ADM acquisition and discrimination module
  • IQC input quality control
  • the remote server system is configured to , via the processor executing software instructions : i . voxelise the image files to produce a 3D re-constructed multi-planar image model within the primary session in the local non-transitory memory; ii . track the interactions with the image model within a remote-database ; iii . publish the image model to an encoded file to be saved to transitory memory; iv . optionally, publish the image model to an arti ficial intelligence system to process and produce a file to be saved to transitory memory; wherein the guest/remote receiver computer system is configured to , via the processor executing software instructions :
  • Figure 2 illustrates another functional flow diagramme of an embodiment of the computer-implemented method for medical image file sharing of Figure 1 ;
  • Figure 4 is a high-level diagrammatic overview representation of an embodiment of the medical image file sharing system of Figure 3 showing a multi-user architecture and hosting platform;
  • Figure 5 illustrates a functional flow diagramme of receiving medical image files , via an acquisition and discrimination module (ADM) which subj ects the image files to input quality control ( IQC ) ;
  • Figure 6 illustrates a functional flow diagramme of the acquisition and discrimination module (ADM) performing IQC via file header inspection to veri fy suitability for measurement ;
  • Figure 7 is a high-level diagrammatic overview representation of software modules comprising one embodiment of the computer- implemented method for medical image file sharing;
  • Figure 8 is a high-level diagrammatic overview representation of an embodiment of a collaboration architecture of the medical image file sharing system.
  • Figure 9 illustrates a high-level architecture diagramme of the medical image file sharing system including software module components installed on a local computer system and in cloud storage .
  • any reference herein to "means” speci fically includes any one or more of a computer programme product for use in a local or dispersed computing system, a computer readable modulated carrier signal for interpretation by a local or dispersed computing system, or a computer readable medium of instructions for enabling a local or dispersed computing system to provide such "means” within the context of the description .
  • such "means” may further expressly comprise any of the hardware and/or software components , independently or in combination, provided for in the description below, as will be understood by the skilled addressee .
  • an application programming interface is a set of subroutine definitions , communication protocols , and tools for building software . In general terms , it is a set of clearly defined methods of communication among various components . Means for facilitating any of the communications or interactions between the respective processing and computer systems and communication networks may be facilitated via suitable API s , as will be readily apparent to the skilled addressee .
  • the present invention provides for a computer- implemented method 10 for medical image file sharing, as well as an associated medical file sharing system 50 .
  • any reference to 3DicomTM and 3Dicom MDTM refers to Applicant ' s trade name for the method 10 and associated system 50 for medical image file sharing, including software applications serving as modules and means for implementing functional aspects within a processing and network framework, as described and illustrated with reference to the accompanying figures .
  • such medical image files generally comprise image data produced via medical imaging modalities , including . j peg/ . png format , . mp4 format , .
  • stl format 3dcm format
  • MCAD Mechanism Computer Aided Des ign
  • non-image date including text and related data in other formats , such as a . pdf format , or the like , as known in the art of medical record keeping .
  • one embodiment o f SDicom MD comprises a launcher application installer which is stored on a SDicom website and which is downloaded by a user and started which installs the programme on the user' s local PC .
  • the launcher then provides a local GUI to the user and communicates with the SDicom server for authentication on first time use with the input of valid user login ( email address ) , initial password and a license key issued by the authentication server .
  • Entered information in the launcher is then compared with the licensing information in the authentication server and a license key installed to the local launcher application. Information is then compared to synchronise the login and access to the main 3Dicom MD application for all subsequent use .
  • the launcher checks all licenses and synchronises them, checks for latest application software release - if not the latest version, provides option to download installation file and install the latest 3Dicom MD application to the local file system, uses the information supplied on account to start the main 3Dicom application, User profilespecific settings can be updated is then supplied to the application upon invocation.
  • the interface as a GUI is invoked from the launcher application and provides the login information to start the application and identify the user, such as a clinician or similar medical professional.
  • the method 10 generally comprises the steps of receiving 12 medical image files, via an acquisition and discrimination module (ADM) , said ADM configured to subject 14 the image files to input quality control (IQC) according to a predetermined protocol and, if IQC is successful, to store 16 said image files on a local database and assigned 18 a unique patient identifier.
  • ADM acquisition and discrimination module
  • IQC input quality control
  • the step of receiving 12 the medical image files comprises receiving said files selectable from a group consisting of local storage, a picture archiving and communication system (PACS) , Secure File Transfer Protocol (SFTP) , a Radiology Information System (RIS) , and removable media.
  • the medical image files are selectable from a group consisting of DICOM files, MRI, CT, XR, MG or PET patient scan files, but variations hereon are possible and anticipated.
  • the step of the ADM subjecting 14 the received image files to input quality control (IQC) according to a predetermined protocol comprises said ADM inspecting header information from DICOM images and comparing header tags between images for consistency.
  • IQC input quality control
  • IQC Input Quality Control
  • all scans or image files imported to the 3Dicom MD application are subject to such Input Quality Control (IQC) check to ensure that the DICOM scan or file is able to be used in the subsequent sessional analysis process and provides a satisfactory output for image quality and measurement.
  • IQC Input Quality Control
  • the IQC step 14 relies on checking specific DICOM tags if a value is present and/or consistent through a series of images comprising such image files. Scans that fail the IQC check will not be available for sessional selection by the user and will trigger an error message indicative of the reason for failure. Some IQC checks will allow the scan to be processed but will inform the user via a warning message of the issue and its impact on the expected output (s) .
  • the process upon import 12 of patient scans to the scan database and local file system comprises decompressing the DICOM file(s) if in compressed format; if any individual file length is greater than 256 characters, the file is skipped, and loading the DICOM file and extracting all DICOM header tags.
  • the 3Dicom MD Measurement function is disabled. Similarly, if any 'slice' in a series of image files or scans is missing in the DICOM scans, then the 3Dicom MD Measurement function is disabled.
  • the measurement algorithm is calculated by using a bed position or DICOM Image Position Patient attribute [0020,0032] to determine the z coordinates of the upper left and corner of the image , in mm; the first row and first column direction cosines are determined with respect to the patient using DICOM Image Orientation [ 0020 , 0037 ] ; the algorithm calculates the average spacing across all slices to the x and y coordinates using Pixel Spacing [ 0028 , 0030 ] of the user-selected points on the 2D Plane View relative to the Z bed position ( Image Position Patient ) ; and the resulting relative di f ference is the output measurement value in mm .
  • the method 10 further generally comprises the step, upon receipt of a user request via the locally-provided GUI , providing a unique patient identi bomb assigned to speci fic image files , creating a primary session 22 where the image files are loaded into local non-transitory memory, typically random-access memory (RAM) .
  • the system uses a local SQLite database and provides a patient list of all studies that pertain to the user and can be selected to open a session for diagnostic analysis .
  • the 3Dicom MD user interface or GUI enables clinicians to view a list of all scans , and then to visualise a scan by opening a session on an individual scan .
  • the method 10 then typically comprises the step of voxelising 24 the received image files or scans to produce a 3D re-constructed multi-planar image model within the primary session in the local non-transitory memory .
  • the step of voxelising 24 comprises sequentially processing the medical image files by assigning each image pixel a 3D coordinate to convert said images into a voxelised image data cube wherein each voxel is represented by an x, y and z axis value , said image data cube forming the 3D re-constructed multi-planar image model within the primary session .
  • Opening a session generally invokes the voxelisation process which creates a 3D model of the scan in local random- access memory (RAM) using the 2D images .
  • scan structured data i . e . the image model
  • the IQC checks are success ful , as described .
  • Scans are opened by the user as a session and when in session both structured image model and image data are loaded to the random-access memory (RAM) of the local computer system or PC .
  • the method 10 then comprises the step of enabling, via the locally-provided GUI , user interaction with said image model or scan structured data in the primary session to enable visualisation and annotation 26 of the image model in substantial real-time .
  • Such user interaction is also captured 28 in local non-transitory memory as sessional analysis information .
  • the step of capturing 28 the user interaction as sessional analysis information comprises capturing and transposing annotations , measurements , segmentation, and graphical markups made via the GUI on any 2D image plane to corresponding coordinates in the voxelised 3D image model .
  • a key action of this function is to transpose the annotations and other graphical markups reflective of their 2D equivalents to the 3D volume model preserving and displaying annotation/markup/measurement ID as well as dimensions , orientation and coordinates .
  • the step of enabling user interaction 26 via the locally-provided GUI with the image model in the primary session in substantial real-time comprises rendering the image model in 3D, enabling navigation of the image model (pan, zoom, rotate ) , enabling viewing the image model in di f ferent planes ( axial , sagittal , coronal ) , enabling manipulating the visualisation (planar intersection, segmentation, density adj ustments ) , adding and/or editing annotations to the image model , capturing images of aspects of the image model , and/or measuring features of the image model .
  • Such user navigation via a GUI is well-known in the art of computer science and may include 2D multi-planar navigation, volume navigation, snapping a 3D visual perspective to pre-defined positions , immersive zoom, immersive camera POV, image density adj ustments & presets , image display, manipulating planar intersects , image and video capture , and the like .
  • a user is able to visualise a 3D- rendered version of the image model , navigate the scan in di f ferent ways (pan, zoom, rotate, zoom) , view the scan in dif ferent planes ( axial , sagittal , coronal ) , manipulate the visualisation (planar intersection, segmentation, density ad ustments ) , add/edit annotations , make measurements .
  • the impact of each user-driven event and update produces a refresh of the scan visualisation and associated information so that the user is able to visually assess the impact as each change as they are made .
  • the method 10 then generally comprises the step of , upon receipt of a collaboration request from either a local user (via the local GUI ) or a remote request from a guest user via a remote GUI , creating 30 a secondary session in remote non-transitory memory of a guest computer system via a communications network, and transmitting the visualisation of the image model and sessional analysis information to the remote secondary ses sion .
  • the method 10 also typically includes a step of providing the remote GUI to enable remote user interaction with said transmitted visualisation with sessional analysis information .
  • the step of creating a secondary session in remote non-transitory memory comprises creating a plurality of distinct secondary sessions in respective remote non-transitory memories to enable collaboration between more than two users .
  • the method 10 includes the step of , upon receipt of the collaboration request , establishing a voice and/or video communication link between the local 42 and remote 54 computer systems .
  • the method 10 includes the step of , upon receipt of a collaboration request , enabling user interaction 42 via the remote GUI with said image model in the primary session to enable visualisation and annotation of the image model by a remote user in substantial real-time .
  • the method 10 also typically comprises the step of overlaying the sessional analysis information onto the visualisation of the image model in substantial real-time for the primary session, and i f active , the secondary session .
  • a user can host a collaborative call or j oin a call as a guest by invitation .
  • Upon receipt of a termination request 34 at least the secondary session is closed and the 3D re-constructed multi-planar image model and sessional analysis information is stored on the local database .
  • all updates and edits to the image model made during the session can be saved and re-opened at a later time .
  • User edits are held in random-access memory during the primary session and saved to local long-term memory on the local file system when the session is closed by the user .
  • the method 10 includes the step of anonymising the visualisation of the image model and sessional analysis information prior to transmission to the secondary session in the remote non-transitory memory .
  • the method includes the step of uploading 44 the image model and sessional analysis information from the local database to networked cloud storage .
  • the method includes the step of subj ecting the image model and/or sessional analysis information to arti ficial intelligence /machine learning (AI /ML ) when uploaded to , or downloaded from, networked cloud storage .
  • AI /ML arti ficial intelligence /machine learning
  • the method 10 includes the step of exchanging the image model and ses sional analysis information with a picture archiving and communication system ( PACS ) .
  • PACS picture archiving and communication system
  • the method 10 may include a step of making asynchronous requests to one or more connected PACS systems, said requests containing relevant, encrypted patient information, to either receive or transmit relevant information via converting the information to PACS-compatible messages such as C-FIND, C-MOVE, C-SEND etc. to retrieve or transmit images, reports, and related documents between the PACS server (s) and the host computer system 52, or the like .
  • FIG. 5 With specific reference to Figures 3, 4 and 7 - 9, there is shown aspects of an associated medical image file sharing system 50 configured to perform the above-described method 10.
  • a system 50 broadly comprises a host computer system 52 typically comprising a processor, the local non-transitory memory, a local database, a network interface and a local display.
  • System 50 also includes at least one guest computer system 54 which is operatively networked with said host computer system 52 via a communications network, such as the Internet, and comprises a processor, the remote non-transitory memory, a display and a network interface.
  • a communications network such as the Internet
  • the host computer system 52 is generally configured, via the processor executing software instructions 60, to: i. receive 12 the medical image files, via an acquisition and discrimination module (ADM) , said ADM configured to subject 14 the image files to input quality control (IQC) according to a predetermined protocol and, if IQC is successful, to store 16 said image files on the local database and assigned 18 a unique patient identifier; ii. upon receipt of a request 20, via a GUI provided on the local display, from a user providing the unique patient identifier, create 22 a primary session where the image files are loaded into the local non-transitory memory; iii.
  • ADM acquisition and discrimination module
  • IQC input quality control
  • voxelise 24 the image files to produce a 3D reconstructed multi-planar image model within the primary session in the local non-transitory memory; iv . enable , via the locally-provided GUI , user interaction 26 with said image model in the primary session to enable visualisation and annotation of the image model in substantial real-time ; v . capture 28 such user interaction in the local non- transitory memory as sessional analysis information; vi .
  • the host computer system 52 processor executes an ADM algorithm subj ecting the received image files to input quality control ( IQC ) according to a predetermined protocol comprising said ADM inspecting header information from DICOM images and comparing header tags between images for consistency .
  • IQC input quality control
  • the host computer system 52 voxelises by sequentially processing the medical image files and assigning each image pixel a 3D coordinate to convert said images into a voxelised image data cube wherein each voxel is represented by an x, y and z axis value , said image data cube forming the 3D re-constructed multi-planar image model within the primary session .
  • the host computer system 52 processor enables user interaction via the locally-provided GUI with the image model in the primary session in substantial real-time by interactively rendering the image model in 3D on the display, enabling navigation of the image model (pan, zoom, rotate ) , enabling viewing the image model in di f ferent planes ( axial , sagittal , coronal ) , enabling manipulating the visualisation (planar intersection, density adj ustments ) , adding and/or editing annotations to the image model , capturing images of aspects of the image model , and/or measuring features of the image model .
  • the host computer system 52 processor is configured, upon receipt of the collaboration request , to establish a voice and/or video communication link between the host and guest computer systems .
  • the host computer system 52 processor is configured to capture the user interaction as sessional analysis information by capturing and transposing annotations , measurements and graphical markups made via the GUI on any 2D image plane to corresponding coordinates in the voxelised 3D image model .
  • the relevant computer system processor is configured to overlay the ses sional analysis information onto the visualisation of the image model in substantial real-time for the primary session, and i f active , the secondary session .
  • the host computer system 52 processor is conf igured to anonymi se the visualisation of the image model and sessional analysis information prior to transmission to the secondary session in the remote non-transitory memory of the guest computer system 54 .
  • the host computer system 52 processor is configured, upon receipt of a collaboration request , to enable user interaction via the remote GUI with said image model in the primary session to enable visualisation and annotation of the image model by a remote user of the guest computer system 54 in substantial real-time .
  • the host computer system 52 processor is configured to create the secondary session in the remote non- transitory memory by creating a plurality of distinct secondary sessions in respective remote non-transitory memories of separate guest computer systems 54 to enable collaboration between more than two users .
  • the host computer system 52 processor is configured to upload the image model and sessional analysis information from the local database to networked cloud storage 58 .
  • the host computer system 52 processor is configured to subj ect the image model and/or sessional analysis information to arti ficial intelligence/machine learning (AI /ML ) when uploaded to , or downloaded from, networked cloud storage .
  • AI /ML arti ficial intelligence/machine learning
  • the host computer system 52 processor is configured to exchange the image model and sessional analysis information with a picture archiving and communication system ( PACS ) .
  • PACS picture archiving and communication system
  • the system may be configured to make asynchronous requests to one or more connected PACS systems , said requests containing relevant , encrypted patient information, to either receive or transmit relevant information via converting the information to PACS-compatible messages such as C-FIND, C-MOVE , C- SEND etc . to retrieve or transmit images , reports , and related documents between the PACS server ( s ) and the host computer system 52 , or the like .
  • a further embodiment of the medical image file trans fer system 50 may comprise a host computer system 52 comprising a processor, local non-transitory memory, a local database , a network interface and a local display; at least one remote server system 58 operatively networked with said host computer system via a communications network and comprising a processor, remote non-transitory memory, a display and a network interface ; and at least one guest/remote receiver computer system 54 operatively networked with said host computer system via a communications network and comprising a processor, remote non-transitory memory, a display and a network interface .
  • the host computer system 52 may be configured to , via the processor executing software instructions , receive medical image files , via an acquisition and discrimination module (ADM) , said ADM configured to subj ect the image files to input quality control ( IQC ) according to a predetermined protocol and, i f IQC is success ful , to store said image files on the local database and assigned a unique patient identi bomb ; upon receipt of a request, via a GUI provided on the local display, from a user providing the unique patient identi fier, create a primary session where the image files are loaded into the local non-transitory memory; optionally anonymise and de-identi fy, the primary session by removing key attributes able to link prior or future sessions ; encrypt and obfuscate the session in such a way that it can only be reconstructed with a unique key; and upload the session to the remote server wherein it will be stored for future retrieval .
  • ADM acquisition and discrimination module
  • the remote server system 58 is then typically configured to , via the processor executing software instructions , voxelise the image files to produce a 3D re-constructed multi-planar image model within the primary session in the local non-transitory memory; track the interactions with the image model within a remote-database ; publish the image model to an encoded file to be saved to transitory memory; and optionally, publish the image model to an arti ficial intelligence system to process and produce a file to be saved to transitory memory .
  • the guest/remote receiver computer system 54 is further generally configured to , via the processor executing software instructions download the trans fer of the voxelised image model from the primary session; enable , via the remote-downloaded locally-provided GUI , user interaction with said image model in the primary session to enable visualisation and annotation of the image model in substantial real-time ; capture such user interaction in the local non-transitory memory as sessional analysis information; download additional files from the remote database memory; enable , via the remote-downloaded locally- provided GUI , user interaction with additional f iles provided by the remote database memory, generally, but not limited to , associated files from the arti f icial intelligence process ; and publish the remote session to an encoded file in remote non- transitory memory .
  • the 3Dicom software application 60 uses a launcher programme to authenticate users , assign the license and check for latest software updates to make new deployments of the software to a locally installed Windows PC or Mac operating system .
  • the 3Dicom system presents a GUI that allows trans fers of images by various methods , including local storage , PACS , SFTP, and USB/removeable media, with structured data loaded into a local SQLite database .
  • DICOM files are also interrogated for input quality control ( IQC ) using a defined protocol and filtering out patient scans where the minimum standard is not met . Once a patient scan has passed all input quality control ( IQC ) checks , the patient data and image data are stored locally on the host PC database and file system .
  • a 3Dicom MD user may then select a patient scan and open a primary session, thereby loading the patient scan image data to memory .
  • the user is able to perform any number of functions in any order and the system responds to each user event with an update of data and GUI refresh in response to that event .
  • the primary session can then be saved whereby all data is then stored locally to the SQLite database and the local file system .
  • the cloud server 58 may be hosted via, for example , Amazon Web Services (AWS ) on an EC2 instance facilitating authentication, l icensing, and collaboration functions such as call control , user settings , DICOM file trans fer, chat server, VoIP server and maintaining call sessions .
  • AWS Amazon Web Services
  • instances of the server 58 are only exposed to the Internet via an API on a load balancer provided by AWS Elastic Bean Stalk (EBS ) which provides end-point termination, auto scaling, and code deployment management .
  • EBS AWS Elastic Bean Stalk
  • a user Whilst in a session, a user can take the role of host and initiate a collaborative call , inviting other 3Dicom users to j oin the call as guests in which an invitation acceptance commences a DICOM study file trans fer between the Host and each of the call Guests .
  • Guest users temporarily receive an anonymised copy of the DICOM scan files to their local file system which is held in memory and cleared at the end of the session .
  • the host and guests can then communicate through various interactive conduits ( Chat , VoIP, screen refresh, capture etc ) with all 3Dicom client software 60 communicating through a cloud-based collaboration server 58 which facilitates the digital , real-time interaction with the scan data in 2D and/or 3D .
  • the present invention provides for a method 10 for medical image file sharing and an associated medical image file sharing system 50 which facilitates sharing of medical image files and image models privately and without signi ficant bandwidth requirements .
  • the present invention allows for a desktop computer system to be used to voxelise and visualise the image files and image model , which is then shareable to, for example, a mobile device without such computing resources and without requiring transmission of the image files or image model, as only a visualisation thereof is transmitted.
  • the transmitted visualisation can also be anonymised before transmission, and is stored on local and/or cloud storage under the unique patient identifier.
  • Applicant further believes it advantageous that the present invention is able to facilitate retrieval of medical files, including images, reports, referrals etc. from mobile, desktop, PACS, VNAs, EMRs either upon manual request or when certain criteria are met, as well as performing Input Quality Control of medical images, as well as anonymisation, encryption, and compression of selected medical files and ingress into cloud-based storage, which happens on an origin or source device.
  • the invention further facilitates the creation of a unique ID / "fingerprint" of a medical image using traditional cryptographic methods, or potentially also blockchain ledgers, as well as voxelisation (3D rendering) of applicable medical image files from DICOM to proprietary 3VXL file type which can be provided upon manual request, or automatic request when certain criteria are met, to a GUI and/or 3rd party program/ recipient .
  • the present invention also enables file storage, with a length of time of storage able to be modified, of medical files in local or cloud-based servers.
  • the present invention further facilitates the transfer of medical files to 3rd party recipients with the ability to, manually or automatically, based on set criteria, determine the end recipient ( s ) , limit the "on-sharing" (ability of recipient to share the file again) of the files by the intended recipient ( s ) , determine the session data / meta-data to be shared with the file(s) , set a time-limit for file retrieval by the recipient ( s ) , anonymise files / medical images at time of transfer, and include instructions for manual, or automatic, analysis of the file(s) .
  • the present invention additionally facilitates the receipt of files from 3rd parties with session data, the transmission of files / images for Al analysis, the creation of an audit trail using the unique ID / fingerprint and a log of the actions taken, being able to visually display an audit trail within a GUI, providing an audit trail to 3rd parties upon manual or automatic request, and the decryption, expansion, and egress of medical files to mobile, desktop, PACS, VNAs, EMRs either upon manual request or when certain criteria are met.
  • the retrieval of reports, amended DICOM files, computer aided design files and other associated media from analysis of medical files / medical images and association of said files to original DICOM patient, study, and/or series is enabled by the invention as described herein.

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  • General Health & Medical Sciences (AREA)
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  • Public Health (AREA)
  • Radiology & Medical Imaging (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
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Abstract

L'invention concerne un procédé mis en œuvre par ordinateur pour un partage de fichier d'image médicale. Le procédé comprend les étapes de réception de fichiers d'images médicales, par l'intermédiaire d'un module d'acquisition et de discrimination (ADM), ledit ADM étant configuré pour soumettre les fichiers d'images à un contrôle de qualité d'entrée (IQC) selon un protocole prédéterminé et, si IQC est réussi, stocker lesdits fichiers d'images sur une base de données locale et assigner un identifiant unique de patient; lors de la réception d'une demande, par l'intermédiaire d'une GUI fournie localement, à partir d'un utilisateur fournissant un tel identifiant unique de patient, créer une session primaire où les fichiers d'image sont chargés dans une mémoire non transitoire locale; voxeliser des fichiers d'image pour produire un modèle d'image multi-plan reconstruit 3D dans une telle session primaire dans la mémoire non transitoire locale ; permettre, par l'intermédiaire de la GUI fournie localement, une interaction d'utilisateur avec ledit modèle d'image dans la session primaire pour permettre la visualisation et l'annotation du modèle d'image en temps réel substantiel ; capturer une telle interaction d'utilisateur dans une mémoire non transitoire locale en tant qu'informations d'analyse sessiale ; lors de la réception d'une demande de collaboration, créer une session secondaire dans une mémoire non transitoire à distance par l'intermédiaire d'un réseau de communication, transmettre la visualisation du modèle d'image et les informations d'analyse sessiale à la session secondaire, et fournir une GUI à distance pour permettre une interaction d'utilisateur à distance avec ladite visualisation transmise avec des informations d'analyse sessiale ; et lors de la réception d'une demande de terminaison, fermer au moins la session secondaire et stocker le modèle d'image multi-plan reconstruit 3D et les informations d'analyse sessiale sur la base de données locale.
PCT/AU2024/051268 2023-11-28 2024-11-28 Système de transfert de fichier médical Pending WO2025111649A1 (fr)

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