US20050002547A1 - Remote interpretation of medical images - Google Patents

Remote interpretation of medical images Download PDF

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US20050002547A1
US20050002547A1 US10803194 US80319404A US2005002547A1 US 20050002547 A1 US20050002547 A1 US 20050002547A1 US 10803194 US10803194 US 10803194 US 80319404 A US80319404 A US 80319404A US 2005002547 A1 US2005002547 A1 US 2005002547A1
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image
medical image
remote view
view station
region
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US10803194
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Jose Torre-Bueno
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Carl Zeiss Microscopy GmbH
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ChromaVision Medical Systems Inc
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/324Management of patient independent data, e.g. medical references in digital format
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/3418Telemedicine, e.g. remote diagnosis, remote control of instruments or remote monitoring of patient carried devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/21Intermediate information storage
    • H04N1/2166Intermediate information storage for mass storage, e.g. in document filing systems
    • H04N1/217Interfaces allowing access to a single user
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/12Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/162User input
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/90Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/99Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals involving fractal coding
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10116X-ray image

Abstract

A remote view station is communicatively coupled to an image server and receives a compressed version of source medical images. The remote view station uncompresses and displays the received medical image. A medical professional, such as a pathologist, can select a region of the displayed medical image. Region information is transmitted back to the image server that applies image analysis operations on a region of the source medical image that corresponds to the selected region of the compressed medical image. In this manner, the data loss that occurs during image compression does not effect the image analysis operations. As such, the image analysis operations produce more accurate results than if the operations were applied by remote view station to the uncompressed image.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application is a continuation-in-part of and claims priority to U.S. application Ser. No. 09/542,091, filed on Apr. 3, 2000, which is incorporated herein in its entirety.
  • BACKGROUND
  • Pathologists typically use microscopes when diagnosing physiological conditions such as cancer, infectious disease and prenatal disorders. Typically, tissue samples on a slide are loaded onto the microscope, the microscope objective or lens focuses on an area of the sample, and the sample is scanned for particular features or objects of interest. In this manner, the microscope helps the pathologist to visually determine the presence of abnormal numbers or types of cells, organelles, organisms or biological markers.
  • Recently, automated microscopes have been integrated into medical imaging systems that include a variety of networked components. The medical imaging system provides an environment for storing and retrieving the medical images produced by the microscopes. The components of the medical imaging system are spread throughout the department or hospital, or even located remotely, and connected by a communication network.
  • An image acquisition device is coupled to the microscope and captures images produced by the microscope. The image acquisition device can include a variety of components. For example, the image acquisition device can include a video camera coupled to a high-speed frame grabber for capturing the stream of video produced by the video camera and generating a series of digital images. Alternatively, the electronic camera can be a megapixel digital camera. The microscope and the image acquisition device can acquire images for a number of different color planes and at several different focal planes. These images can be stitched together to form a two-dimensional or three-dimensional composite image. As a result of the combination, and because the images are typically in color and at high-resolution, the composite images place significant storage and bandwidth requirements on the medical imaging system. For example, a composite image for a single tissue slide can often exceed a gigabyte in size.
  • Image storage and archival devices provide a central library for storing the medical images captured by the image acquisition device. Image storage devices include one or more databases and image servers for fast access to recently acquired images. Archival devices, such as optical disc jukeboxes and tape backup systems, provide long-term storage. When a pathologist wishes to view an archived image, the image is automatically “migrated” from the corresponding archival device to one of the image storage devices.
  • Diagnostic quality view stations display the images captured by the image acquisition system. In order to assist the pathologist in interpreting a medical image, a view station is able to perform a variety of image analysis operations on the medical image for the purposes of diagnosis. Unlike other types of image processing, image analysis operations are not used to manipulate or produce another image from a subject image, but rather to analyze the information in the subject image to produce a “non-image” result, such as a fixed number (or “score”), often falling within a predetermined range. For example, the pathologist at the view stations may invoke algorithms to perform densitometry on selected regions of the medical image in order to identify concentration of a particular analyte within the tissue sample. Other image analysis operations are useful for finding objects within the image such as the nuclei of the cells, computing an integrated optical density for the nuclei of the cells and reporting the number of molecules per cell.
  • SUMMARY
  • In general, the invention facilitates the remote interpretation of medical images. In order to facilitate the timely diagnosis of a tissue sample, it is desirable that a medical professional, such as a pathologist, be able to remotely view and interpret a medical image. The immense size of a medical image for a single tissue sample typically makes remote viewing unworkable due to bandwidth constraints. Compression algorithms can produce an image suitable for transmission, but the data lost during compression can lead to inaccurate results from the image analysis operations.
  • According to one aspect, the invention is directed to a system in which a remote view station is communicatively coupled to an image server and receives a compressed version of a source medical image. The remote view station uncompresses and displays the received medical image. The remote view station selects a region of the displayed medical image as a function of input received from a medical professional, such as a pathologist. Based on the input, the remote view station transmits region information, such as a series of pixel coordinates, back to the image server. The image server applies image analysis operations to a region of the source medical image that corresponds to the selected region of the compressed medical image. In this manner, the data loss that occurs during image compression does not effect the image analysis operations. As such, the image analysis operations produce more accurate results than if the operations were applied by the remote view station on the compressed image.
  • In another aspect, the invention is directed to a method for remotely interpreting medical images. According to the method, a compressed medical image is generated from a source medical image and transmitted from an image server to a remote view station for display. In one implementation, the compressed medical image is transmitted over a global packet-switched network such as the Internet. A region of the medical image displayed by the remote view station is selected in response to input from a medical professional. Region information, defining the selected region of the displayed medial image, is transmitted from the remote view station back to the image server. Based on the region information, image analysis operations are applied to a corresponding region of the source medical image. A resulting score is communicated to the remote view station for display. A diagnosis is received from the remote view station and associated with the source medical image in a database maintained by the image server.
  • Various embodiments of the invention are set forth in the accompanying drawings and the description below. Other features and advantages of the invention will become apparent from the description, the drawings, and the claims.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a block diagram providing a high-level illustration of the various components of the invention.
  • FIG. 2 is a flowchart illustrating one embodiment of a process for remotely interpreting medical images.
  • FIG. 3 is a block diagram illustrates one embodiment of a computer suitable for implementing the various embodiments of the invention.
  • DETAILED DESCRIPTION
  • FIG. 1 is a block diagram illustrating a system 10 that facilitates remotely viewing and interpreting medical images. System 10 includes remote view station 26 this is communicatively coupled to medical imaging system (MIS) 12 by network 20, which represents any packet-switched network such as a local area network or the Internet. MIS 12 includes image acquisition devices 14 that represent any medical imaging device that generates digital medical images, such as an electronic camera used in conjunction with an automated microscope. Other image acquisition devices include computed tomography (CT), nuclear medicine, magnetic resonance imaging (MRI), ultrasound and X-ray devices. Image server 24 stores the images that are generated by image acquisition device 14 and, upon request, communicates the images to view stations 16 for display. Using view stations 16, a medical professional, such as a pathologist, can perform a variety of image analysis techniques on selected regions to assist in rendering a diagnosis.
  • As described in detail below, image server 24 of MIS 12 communicates compressed medical images to remote view station 26 for interpretation by a medical professional. Using a network software application, such as a web browser, the medical professional interacts with remote view station 26 to select various regions of interest within the image. Based on the selection, image server 24 applies image analysis functions directly to the source medical image stored on image server 24, thereby generating a more accurate score than if applied by remote view station 26 to the medical image after compression. The resultant score produced by the image analysis operations is communicated to remote view station 26 to assist the medical professional in interpreting the medical image and rendering a diagnosis.
  • FIG. 2 is a flow chart illustrating one implementation of a process 28 that facilitates the interpretation of medical images via remote view station 26. Using a network software application the medical professional interacts with remote view station 26, accesses MIS 12 and receives a list of cases that are marked for review, i.e., cases in which images have been acquired by image acquisition devices 14 but have not been reviewed by a medical professional (30). Upon reviewing the list displayed by remote view station 26, the medical professional selects one of the cases for review (32).
  • Based on the selection, image server 24 compresses medical images associated with the case and communicates the compressed images to remote view station 26 via network 20 (34). Remote view station 26 decompresses the images and displays the uncompressed images for review by the medical professional (36). The image server 24 may use a lossy compression technique, e.g., JPEG. Such techniques attempt to eliminate redundant or unnecessary information. Consequently, in lossy compression, some information is lost, and the displayed image is not a pixel-by-pixel duplicate of the original source image stored on image server 24. Several algorithms, however, are known that can achieve a compression ratio, such that the compressed image uses relatively low bandwidth, without significantly changing the visual representation of the image. Therefore, compressing the image can be effectively lossless with respect to human vision. For example, it has been found that both JPEG compression and fractal image compression, when set for to moderate compression, result in images suitable for transmission without resulting in data loss perceptible with human vision.
  • Using a pointing device, such as a light pen, mouse or track ball, the medical professional selects one or more regions of interest. The medical professional can tag a region for image analysis or can request that image server 24 transmit image data for the selected region using a lower compression setting. For example, the medical professional can direct image server 24 to transmit an image using low compression or even to transmit an uncompressed pixel-by-pixel duplicate of the selected region. Remote view station 26 encodes the shape and size of the selected region and transmits the region information to MIS 12 by network 20 (38). The region information defines the boundaries of the selected regions and, in one implementation, is a set of pixel coordinates defining the outlines of the selected regions. As such, the region information typically comprises a small amount information and can be quickly transmitted to image server 24.
  • If the medical professional requests that image server 24 transmit image data for a region of interest using a lower compression setting, or no compression, then image server 24 extracts the corresponding pixel data from the source image and communicates the pixel data to remote view station 26 (40). In this fashion, the medical professional can view regions of interest at higher resolution, or even a pixel-per-pixel duplicate, without requiring that image server 24 transmit the entire source image across network 20. Upon viewing the region of interest, the medical professional can tag the region for image analysis or can select sub-regions of interest. In an alternative embodiment, the image server 24 may calculate “difference data” for the selected region, e.g., data lost during the lossy compression operation for the selected region. The image server may then transmit the difference data to the remote view station 26. The remote view station 26 may then use the difference data and compressed (and/or decompressed) image file to reconstruct an image of the selected region of higher resolution for display at the remote view station 26. By sending only the difference data, the amount of data transmitted over the network may be significantly reduced, thereby reducing network traffic and transmission times.
  • If the medical professional tags a selected region for image analysis, image server 24 executes the requested image analysis operation on the corresponding source medical image (42). More specifically, image server 24 analyzes the region information received from remote view station 26 and applies the image analysis operation to a subset of the pixel data of the source image. The subset pixel data is selected based on the boundaries defined by the region information received from remote view station 26. In this manner, the image analysis operation produces a more accurate score than if the operation were applied by remote view station 26 to the image that has been compressed for transmission and then uncompressed for display at the remote view station. As such, the data loss that occurs during compression does not effect the image analysis.
  • Image server 24 communicates the scores for each region to remote view station 26 for display to the medical professional (44). Based on the visual display of the medical image as well as the scores associated with regions of interest, the medical professional interprets the medical image and renders a diagnosis. For example, the medical professional may determine that a particular tissue sample is cancerous. Remote view station 26 communicates the diagnosis to MIS 12 for association with the appropriate case within a database maintained by image server 24 (46).
  • The invention can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations thereof. Furthermore, the invention can be implemented in one or more computer programs that are executable within an operating environment of a programmable system embodied and tangibly stored in a machine-readable storage device.
  • FIG. 3 illustrates an example of a computer 100 suitable for use as view station 26 in order to implement or perform various embodiments of the invention. As shown in FIG. 3, the computer 100 includes a processor 112 that in one embodiment belongs to the PENTIUM® family of microprocessors manufactured by the Intel Corporation of Santa Clara, Calif. However, computer 100 can be implemented on computers based upon other microprocessors, such as the MIPS® family of microprocessors from the Silicon Graphics Corporation, the POWERPC® family of microprocessors from both the Motorola Corporation and the IBM Corporation, the PRECISION ARCHITECTURE® family of microprocessors from the Hewlett-Packard Company, the SPARC® family of microprocessors from the Sun Microsystems Corporation, or the ALPHA® family of microprocessors from the Compaq Computer Corporation.
  • Computer 100 includes system memory 113, including read only memory (ROM) 114 and random access memory (RAM) 115, which is connected to the processor 112 by a system data/address bus 116. ROM 114 represents any device that is primarily read-only including electrically erasable programmable read-only memory (EEPROM), flash memory, etc. RAM 115 represents any random access memory such as Synchronous Dynamic Random Access Memory.
  • Within the computer 100, input/output bus 118 is connected to the data/address bus 116 via bus controller 119. In one embodiment, input/output bus 118 is implemented as a standard Peripheral Component Interconnect (PCI) bus. The bus controller 119 examines all signals from the processor 112 to route the signals to the appropriate bus. Signals between the processor 112 and the system memory 113 are merely passed through the bus controller 119. However, signals from the processor 112 intended for devices other than system memory 113 are routed onto the input/output bus 118.
  • Various devices are connected to the input/output bus 118 including hard disk drive 120, floppy drive 121 that is used to read floppy disk 151, and optical drive 122, such as a CD-ROM drive that is used to read an optical disk 152. The video display 124 or other kind of display device is connected to the input/output bus 118 via a video adapter 125 and preferably is a high-resolution display suitable for viewing medical images. Computer 100 also includes a modem 129 and network interface 53 for communicating over network 20 via either a wired or wireless connection.
  • A medical professional enter commands and information into the computer 100 by using a keyboard 140 and/or pointing device, such as a mouse 142, which are connected to bus 118 via input/output ports 128. Other types of pointing devices (not shown in FIG. 1) include track pads, track balls, joysticks, data gloves, head trackers, and other devices suitable for positioning a cursor on the video display 124.
  • Software applications 136 and data are typically stored via one of the memory storage devices, which may include the hard disk 120, floppy disk 151, CD-ROM 152 and are copied to RAM 115 for execution. Operating system 135 executes software applications 136 and carries out instructions issued by the user. The Basic Input/Output System (BIOS) 117 for the computer 100 is stored in ROM 114 and is loaded into RAM 115 upon booting. BIOS 117 is a set of basic executable routines that help transfer information between the computing resources within the computer 100.
  • A number of embodiments have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. For example, blocks in the flowchart may be skipped or performed out of order and still produce desirable results. Accordingly, other embodiments are within the scope of the following claims.

Claims (24)

1. A method comprising:
generating a compressed medical image from a source medical image at a first location using a lossy compression operation;
transmitting the compressed medical image to a remote view station at a second location for display;
decompressing the compressed image file at the remote view station;
selecting a region of the decompressed medical image at the second location; and
at the first location, applying image analysis operations to a region of the source medical image corresponding to the selected region of the decompressed medical image.
2. The method of claim 1, wherein transmitting the compressed medical image includes transmitting the compressed medical image over a global packet-switched network.
3. The method of claim 1, further comprising:
transmitting region information separate from the compressed medical image from the remote view station to an image server at the first location, wherein the region information defines the selected region of the displayed medical image.
4. The method of claim 3, wherein the region information comprises pixel coordinates.
5. The method of claim 3, further comprising:
at the first location, receiving from the remote view station a request for improved resolution of the selected region;
determining image data to send to the remote view station to provide improved resolution of the selected region; and
sending said image data to the remote view station.
6. The method of claim 5, wherein said determining the image data comprises:
identifying pixel data in the source image corresponding to the selected region in the displayed medical image.
7. The method of claim 5, wherein said determining the image data comprises:
calculating image data lost in the lossy compression operation.
8. The method of claim 1, wherein applying the image analysis operations includes outputting a score and communicating the score to the remote view station for display.
9. A system comprising:
an image server at a first location to store a source medical image and to generate a compressed medical image from the source medical image using a lossy compression operation;
a remote view station at a second location communicatively coupled to the image server to receive the compressed medical image, said remote view station including
a decoder operative to decompress the compressed medical image to generate a decompressed medical image,
a display to display the decompressed medical image, and
an input device to enable selection of a region of the decompressed medical image; and
wherein the image server is operative to perform an image analysis operation on a region of the source medical image that corresponds to a selected region of the decompressed medical image.
10. The system of claim 9, the remote view station is communicatively coupled to the image server via a global packet-switched network.
11. The system of claim 9, wherein the remote view station is operative to transmit region information separate from the compressed medical to the image server, wherein the region information defines the selected region of the decompressed medical image.
12. The system of claim 11, wherein the region information comprises pixel coordinates.
13. The system of claim 11, wherein the image server is operative to:
receive from the remote view station a request for improved resolution of the selected region;
determine image data to send to the remote view station to provide improved resolution of the selected region; and
send said image data to the remote view station.
14. The system of claim 13, wherein said determining the image data comprises:
identifying pixel data in the source image corresponding to the selected region in the displayed medical image.
15. The system of claim 13, wherein said determining the image data comprises:
calculating image data lost in the lossy compression operation.
16. The system of claim 9, wherein the image server is further operative to:
output a score; and
communicate the score to the remote view station for display.
17. A computer program comprising:
generating a compressed medical image from a source medical image at a first location using a lossy compression operation;
transmitting the compressed medical image to a remote view station at a second location for display;
decompressing the compressed image file at the remote view station;
selecting a region of the decompressed medical image at the second location; and
at the first location, applying image analysis operations to a region of the source medical image corresponding to the selected region of the decompressed medical image.
18. The computer program of claim 17, wherein transmitting the compressed medical image includes transmitting the compressed medical image over a global packet-switched network.
19. The computer program of claim 17, further comprising:
transmitting region information separate from the compressed medical image from the remote view station to an image server at the first location, wherein the region information defines the selected region of the displayed medical image.
20. The computer program of claim 19, wherein the region information comprises pixel coordinates.
21. The computer program of claim 19, further comprising:
at the first location, receiving from the remote view station a request for improved resolution of the selected region;
determining image data to send to the remote view station to provide improved resolution of the selected region; and
sending said image data to the remote view station.
22. The computer program of claim 21, wherein said determining the image data comprises:
identifying pixel data in the source image corresponding to the selected region in the displayed medical image.
23. The computer program of claim 21, wherein said determining the image data comprises:
calculating image data lost in the lossy compression operation.
24. The computer program of claim 17, wherein applying the image analysis operations includes outputting a score and communicating the score to the remote view station for display.
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Cited By (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030007674A1 (en) * 2001-04-27 2003-01-09 Osamu Tsujii Image processing apparatus and method
US7027628B1 (en) * 2000-11-14 2006-04-11 The United States Of America As Represented By The Department Of Health And Human Services Automated microscopic image acquisition, compositing, and display
US20060092468A1 (en) * 2000-11-06 2006-05-04 Hiroyuki Matsushima Method of and device for image processing, image forming device, and computer product
US20070239485A1 (en) * 2006-02-01 2007-10-11 Sroub Brian J System and method for providing telediagnostic services
US20080132781A1 (en) * 2006-11-30 2008-06-05 Thomas Redel Workflow of a service provider based CFD business model for the risk assessment of aneurysm and respective clinical interface
US20080130967A1 (en) * 2006-12-01 2008-06-05 Microsoft Corporation Compression and decompression of medical images
US20080267473A1 (en) * 2007-04-24 2008-10-30 Microsoft Corporation Medical image acquisition error detection
US20080275736A1 (en) * 2007-05-04 2008-11-06 Siemens Medical Solutions Usa, Inc. System of Picture Archiving and Communication System With Message Broadcasting Mechanism
US20090169119A1 (en) * 2007-12-03 2009-07-02 Samplify Systems, Inc. Compression and decompression of computed tomography data
US20100045698A1 (en) * 2008-08-21 2010-02-25 Applied Imaging Corporation Client Side Multi-Component Image Composition
US20100061505A1 (en) * 2008-09-11 2010-03-11 Samplify Systems, Inc. Edge detection for computed tomography projection data compression
US20100070836A1 (en) * 2008-09-11 2010-03-18 Samplify Systems, Inc. Adaptive compression of computed tomography projection data
US20100128949A1 (en) * 2008-11-26 2010-05-27 Samplify Systems, Inc. Compression and storage of projection data in a computed tomography system
US20100253777A1 (en) * 2009-04-03 2010-10-07 Hon Hai Precision Industry Co., Ltd. Video monitoring system, image encoder and encoding method thereof
US20110206249A1 (en) * 2010-02-22 2011-08-25 Canon Kabushiki Kaisha Transmission of medical image data
US20120243753A1 (en) * 2007-06-06 2012-09-27 Aperio Technologies, Inc. System and Method for Assessing Image Interpretability in Anatomic Pathology
US20120323118A1 (en) * 2011-06-17 2012-12-20 Carnegie Mellon University Physics based image processing and evaluation process of perfusion images from radiology imaging

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2833132B1 (en) * 2001-11-30 2004-02-13 Eastman Kodak Co A method for selecting and recording an interest about a digital still image
FR2833131B1 (en) * 2001-11-30 2004-02-13 Eastman Kodak Co Method and system for displaying a obtimiser of interest subject in a digital image
US8156210B2 (en) * 2002-11-27 2012-04-10 Ge Medical Systems Global Technology Company Workflow for computer aided detection
US20050114892A1 (en) * 2003-11-26 2005-05-26 Peter Chan Low orbit satellite communication with mobile medical equipment incorporating global positioning system
US7870284B2 (en) * 2005-12-29 2011-01-11 Cytyc Corporation Scalable architecture for maximizing slide throughput
WO2009117419A3 (en) * 2008-03-17 2009-12-10 Worcester Polytechnic Institute Virtual interactive system for ultrasound training
US20100202510A1 (en) * 2009-02-09 2010-08-12 Kyle Albert S Compact real-time video transmission module
US8811695B2 (en) * 2010-12-14 2014-08-19 General Electric Company Methods, apparatus and articles of manufacture to adaptively reconstruct medical diagnostic images
US20120165661A1 (en) * 2010-12-23 2012-06-28 Volcano Corporation Integrated system architectures and methods of use
US9230154B2 (en) 2011-01-24 2016-01-05 Nec Corporation Information processing apparatus, method, and storage medium for assisting with a diagnosis based on a tissue sample
US8600182B2 (en) * 2011-03-04 2013-12-03 Sony Corporation Method and apparatus for compression of image data based on display parameters
WO2012129401A1 (en) * 2011-03-23 2012-09-27 Hologic, Inc. Method for automatically seeding previously-classified images among images of objects of interest from a specimen
US8799358B2 (en) 2011-11-28 2014-08-05 Merge Healthcare Incorporated Remote cine viewing of medical images on a zero-client application
US9471747B2 (en) 2012-01-06 2016-10-18 Upmc Apparatus and method for viewing medical information
US9545206B2 (en) 2012-08-16 2017-01-17 Toshiba Medical Systems Corporation Non-contrast MRI with differentiation of ischemic, infarct and normal tissue
US8977024B1 (en) * 2014-01-31 2015-03-10 Afraxis, Inc. Distributed anatomical image analysis

Citations (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5428690A (en) * 1991-09-23 1995-06-27 Becton Dickinson And Company Method and apparatus for automated assay of biological specimens
US5432871A (en) * 1993-08-04 1995-07-11 Universal Systems & Technology, Inc. Systems and methods for interactive image data acquisition and compression
US5469353A (en) * 1993-11-26 1995-11-21 Access Radiology Corp. Radiological image interpretation apparatus and method
US5586160A (en) * 1995-03-20 1996-12-17 The Regents Of The University Of California Automated analysis for microcalcifications in high resolution digital mammograms
US5646677A (en) * 1995-02-23 1997-07-08 Motorola, Inc. Method and apparatus for interactively viewing wide-angle images from terrestrial, space, and underwater viewpoints
US5737446A (en) * 1996-09-09 1998-04-07 Hughes Electronics Method for estimating high frequency components in digitally compressed images and encoder and decoder for carrying out same
US5740267A (en) * 1992-05-29 1998-04-14 Echerer; Scott J. Radiographic image enhancement comparison and storage requirement reduction system
US5851186A (en) * 1996-02-27 1998-12-22 Atl Ultrasound, Inc. Ultrasonic diagnostic imaging system with universal access to diagnostic information and images
US5854851A (en) * 1993-08-13 1998-12-29 Sophis View Technologies Ltd. System and method for diagnosis of living tissue diseases using digital image processing
US5966465A (en) * 1994-09-21 1999-10-12 Ricoh Corporation Compression/decompression using reversible embedded wavelets
US6006191A (en) * 1996-05-13 1999-12-21 Dirienzo; Andrew L. Remote access medical image exchange system and methods of operation therefor
US6031929A (en) * 1996-07-18 2000-02-29 University Of Pittsburgh Image facsimile with real time image segmentation
US6058322A (en) * 1997-07-25 2000-05-02 Arch Development Corporation Methods for improving the accuracy in differential diagnosis on radiologic examinations
US6125194A (en) * 1996-02-06 2000-09-26 Caelum Research Corporation Method and system for re-screening nodules in radiological images using multi-resolution processing, neural network, and image processing
US6226392B1 (en) * 1996-08-23 2001-05-01 Bacus Research Laboratories, Inc. Method and apparatus for acquiring and reconstructing magnified specimen images from a computer-controlled microscope
US6226636B1 (en) * 1998-11-20 2001-05-01 Philips Electronics North America Corp. System for retrieving images using a database
US6281874B1 (en) * 1998-08-27 2001-08-28 International Business Machines Corporation Method and system for downloading graphic images on the internet
US6314452B1 (en) * 1999-08-31 2001-11-06 Rtimage, Ltd. System and method for transmitting a digital image over a communication network
US6778709B1 (en) * 1999-03-12 2004-08-17 Hewlett-Packard Development Company, L.P. Embedded block coding with optimized truncation
US7146372B2 (en) * 1997-03-03 2006-12-05 Olympus America Inc. Method and apparatus for creating a virtual microscope slide

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5229698A (en) 1990-08-06 1993-07-20 Cincinnati Milacron Inc. Method and apparatus for sub-span interpolation
US5737445A (en) * 1995-04-20 1998-04-07 The United States Of America As Represented By The United States Department Of Energy Automated feature detection and identification in digital point-ordered signals
JPH09117417A (en) 1995-10-27 1997-05-06 Gemetsukusu:Kk Phthologic image telediagnosis system
JPH09200756A (en) 1996-01-17 1997-07-31 Kubota Corp Method, device for compressing image data, method, device for transmitting/receiving image data and image data receiver
US6404906B2 (en) * 1997-03-03 2002-06-11 Bacus Research Laboratories,Inc. Method and apparatus for acquiring and reconstructing magnified specimen images from a computer-controlled microscope
US6115486A (en) * 1996-11-06 2000-09-05 Quinton Instrument Company Teleradiology system for the storage and transmission of angiographic and related image sequences
US6261103B1 (en) * 1999-04-15 2001-07-17 Cb Sciences, Inc. System for analyzing and/or effecting experimental data from a remote location
US6621918B1 (en) * 1999-11-05 2003-09-16 H Innovation, Inc. Teleradiology systems for rendering and visualizing remotely-located volume data sets

Patent Citations (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5428690A (en) * 1991-09-23 1995-06-27 Becton Dickinson And Company Method and apparatus for automated assay of biological specimens
US5740267A (en) * 1992-05-29 1998-04-14 Echerer; Scott J. Radiographic image enhancement comparison and storage requirement reduction system
US5432871A (en) * 1993-08-04 1995-07-11 Universal Systems & Technology, Inc. Systems and methods for interactive image data acquisition and compression
US5854851A (en) * 1993-08-13 1998-12-29 Sophis View Technologies Ltd. System and method for diagnosis of living tissue diseases using digital image processing
US5469353A (en) * 1993-11-26 1995-11-21 Access Radiology Corp. Radiological image interpretation apparatus and method
US5966465A (en) * 1994-09-21 1999-10-12 Ricoh Corporation Compression/decompression using reversible embedded wavelets
US5646677A (en) * 1995-02-23 1997-07-08 Motorola, Inc. Method and apparatus for interactively viewing wide-angle images from terrestrial, space, and underwater viewpoints
US5586160A (en) * 1995-03-20 1996-12-17 The Regents Of The University Of California Automated analysis for microcalcifications in high resolution digital mammograms
US6125194A (en) * 1996-02-06 2000-09-26 Caelum Research Corporation Method and system for re-screening nodules in radiological images using multi-resolution processing, neural network, and image processing
US5851186A (en) * 1996-02-27 1998-12-22 Atl Ultrasound, Inc. Ultrasonic diagnostic imaging system with universal access to diagnostic information and images
US6006191A (en) * 1996-05-13 1999-12-21 Dirienzo; Andrew L. Remote access medical image exchange system and methods of operation therefor
US6031929A (en) * 1996-07-18 2000-02-29 University Of Pittsburgh Image facsimile with real time image segmentation
US6226392B1 (en) * 1996-08-23 2001-05-01 Bacus Research Laboratories, Inc. Method and apparatus for acquiring and reconstructing magnified specimen images from a computer-controlled microscope
US5737446A (en) * 1996-09-09 1998-04-07 Hughes Electronics Method for estimating high frequency components in digitally compressed images and encoder and decoder for carrying out same
US7146372B2 (en) * 1997-03-03 2006-12-05 Olympus America Inc. Method and apparatus for creating a virtual microscope slide
US6058322A (en) * 1997-07-25 2000-05-02 Arch Development Corporation Methods for improving the accuracy in differential diagnosis on radiologic examinations
US6281874B1 (en) * 1998-08-27 2001-08-28 International Business Machines Corporation Method and system for downloading graphic images on the internet
US6226636B1 (en) * 1998-11-20 2001-05-01 Philips Electronics North America Corp. System for retrieving images using a database
US6778709B1 (en) * 1999-03-12 2004-08-17 Hewlett-Packard Development Company, L.P. Embedded block coding with optimized truncation
US6314452B1 (en) * 1999-08-31 2001-11-06 Rtimage, Ltd. System and method for transmitting a digital image over a communication network

Cited By (38)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7483162B2 (en) * 2000-11-06 2009-01-27 Ricoh Company, Ltd. Method of and device for image processing, image forming device, and computer product
US20060092468A1 (en) * 2000-11-06 2006-05-04 Hiroyuki Matsushima Method of and device for image processing, image forming device, and computer product
US7027628B1 (en) * 2000-11-14 2006-04-11 The United States Of America As Represented By The Department Of Health And Human Services Automated microscopic image acquisition, compositing, and display
US7305109B1 (en) 2000-11-14 2007-12-04 The Government of the United States of America as represented by the Secretary of Health and Human Services, Centers for Disease Control and Prevention Automated microscopic image acquisition compositing, and display
US20050213802A1 (en) * 2001-04-27 2005-09-29 Canon Kabushiki Kaisha Image processing apparatus and method
US7031506B2 (en) * 2001-04-27 2006-04-18 Canon Kabushiki Kaisha Image processing apparatus and method
US20030007674A1 (en) * 2001-04-27 2003-01-09 Osamu Tsujii Image processing apparatus and method
US7570790B2 (en) 2001-04-27 2009-08-04 Canon Kabushiki Kaisha Image processing method and apparatus for acquiring higher resolution image data for a region of interest from a data stream
US20070239485A1 (en) * 2006-02-01 2007-10-11 Sroub Brian J System and method for providing telediagnostic services
US20080132781A1 (en) * 2006-11-30 2008-06-05 Thomas Redel Workflow of a service provider based CFD business model for the risk assessment of aneurysm and respective clinical interface
US8503741B2 (en) * 2006-11-30 2013-08-06 Siemens Aktiengesellschaft Workflow of a service provider based CFD business model for the risk assessment of aneurysm and respective clinical interface
US20080130967A1 (en) * 2006-12-01 2008-06-05 Microsoft Corporation Compression and decompression of medical images
US7697741B2 (en) 2006-12-01 2010-04-13 Microsoft Corporation Compression and decompression of medical images
US7860286B2 (en) 2007-04-24 2010-12-28 Microsoft Corporation Medical image acquisition error detection
US20080267473A1 (en) * 2007-04-24 2008-10-30 Microsoft Corporation Medical image acquisition error detection
US20080275736A1 (en) * 2007-05-04 2008-11-06 Siemens Medical Solutions Usa, Inc. System of Picture Archiving and Communication System With Message Broadcasting Mechanism
US8737714B2 (en) * 2007-06-06 2014-05-27 Leica Biosystems Imaging, Inc. System and method for assessing image interpretability in anatomic pathology
US20140112560A1 (en) * 2007-06-06 2014-04-24 Leica Biosystems Imaging, Inc. System and Method For Assessing Image Interpretability in Anatomic Pathology
US20120243753A1 (en) * 2007-06-06 2012-09-27 Aperio Technologies, Inc. System and Method for Assessing Image Interpretability in Anatomic Pathology
US9117256B2 (en) * 2007-06-06 2015-08-25 Leica Biosystems Imaging, Inc. System and method for assessing image interpretability in anatomic pathology
US7844097B2 (en) 2007-12-03 2010-11-30 Samplify Systems, Inc. Compression and decompression of computed tomography data
US20090169119A1 (en) * 2007-12-03 2009-07-02 Samplify Systems, Inc. Compression and decompression of computed tomography data
EP2159726A1 (en) 2008-08-21 2010-03-03 Genetix Corporation Client side multi-component image composition
US20100045698A1 (en) * 2008-08-21 2010-02-25 Applied Imaging Corporation Client Side Multi-Component Image Composition
US8400470B2 (en) 2008-08-21 2013-03-19 Genetix Corp Client side multi-component image composition
US7916830B2 (en) * 2008-09-11 2011-03-29 Samplify Systems, Inc. Edge detection for computed tomography projection data compression
US7852977B2 (en) 2008-09-11 2010-12-14 Samplify Systems, Inc. Adaptive compression of computed tomography projection data
US20100070836A1 (en) * 2008-09-11 2010-03-18 Samplify Systems, Inc. Adaptive compression of computed tomography projection data
US20100061505A1 (en) * 2008-09-11 2010-03-11 Samplify Systems, Inc. Edge detection for computed tomography projection data compression
US8045811B2 (en) 2008-11-26 2011-10-25 Samplify Systems, Inc. Compression and storage of projection data in a computed tomography system
US8151022B2 (en) 2008-11-26 2012-04-03 Simplify Systems, Inc. Compression and storage of projection data in a rotatable part of a computed tomography system
US20100128998A1 (en) * 2008-11-26 2010-05-27 Samplify Systems, Inc. Compression and storage of projection data in a rotatable part of a computed tomography system
US20100128949A1 (en) * 2008-11-26 2010-05-27 Samplify Systems, Inc. Compression and storage of projection data in a computed tomography system
US20100253777A1 (en) * 2009-04-03 2010-10-07 Hon Hai Precision Industry Co., Ltd. Video monitoring system, image encoder and encoding method thereof
US8571280B2 (en) 2010-02-22 2013-10-29 Canon Kabushiki Kaisha Transmission of medical image data
US20110206249A1 (en) * 2010-02-22 2011-08-25 Canon Kabushiki Kaisha Transmission of medical image data
US20120323118A1 (en) * 2011-06-17 2012-12-20 Carnegie Mellon University Physics based image processing and evaluation process of perfusion images from radiology imaging
US9179881B2 (en) * 2011-06-17 2015-10-10 Carnegie Mellan University Physics based image processing and evaluation process of perfusion images from radiology imaging

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