WO2004081873A2 - System and method for performing a virtual endoscopy - Google Patents
System and method for performing a virtual endoscopy Download PDFInfo
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- WO2004081873A2 WO2004081873A2 PCT/US2004/007300 US2004007300W WO2004081873A2 WO 2004081873 A2 WO2004081873 A2 WO 2004081873A2 US 2004007300 W US2004007300 W US 2004007300W WO 2004081873 A2 WO2004081873 A2 WO 2004081873A2
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- Prior art keywords
- lumen
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- region growing
- mpr
- rendering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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; CALCULATING OR 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
- G06T2207/30028—Colon; Small intestine
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06T2207/30061—Lung
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2210/00—Indexing scheme for image generation or computer graphics
- G06T2210/41—Medical
Definitions
- the present invention relates to performing a virtual endoscopy and, more particularly, to performing a virtual endoscopy using multiplanar reconstruction (MPR) and three-dimensional (3D) renderings of a virtual endoscopic image.
- MPR multiplanar reconstruction
- 3D three-dimensional
- Virtual endoscopy is a method of diagnosis using computer processing of three-dimensional (3D) image datasets such as, computerized tomography (CT) or magnetic resonance imaging (MRI) scans, to provide simulated visualizations of patient specific organs similar to those produced by standard invasive endoscopic procedures.
- 3D three-dimensional
- MRI magnetic resonance imaging
- Virtual endoscopy has been applied to many endoscopic procedures including bronchoscopy, coionoscopy, pancreatoscopy, laryngoscopy, and otoscopy.
- 3D images are created to simulate images coming from, for example, a fiber optic endoscope.
- a lumen such as a colon
- a perspective projection typically at a wide angle such as 110 degrees.
- the resulting images are useful to view the inner surface of the lumen, information on the outer surface of the lumen is typically not visible.
- a wide-angle perspective projection e.g., 100 or 110 degrees
- features such as tumors that may be hidden behind folds and curves in the lumen are not observed.
- the present invention overcomes the foregoing and other problems encountered in the known teachings by providing a system and method for performing a virtual endoscopy.
- a method for performing a virtual endoscopy comprises the steps of: calculating a distance map using three-dimensional (3D) data of a lumen; calculating a multiplanar reconstruction (MPR) of the lumen; performing a region growing on the MPR of the lumen; marking data from the region growing; and performing a 3D rendering of the marked data from the region growing.
- 3D three-dimensional
- MPR multiplanar reconstruction
- a method for performing a virtual endoscopy comprises the steps of: calculating a distance map using 3D data of a lumen; calculating an MPR of the lumen, wherein the MPR is calculated orthogonal to the lumen at an endoscope position; performing a first region growing on the MPR of the lumen at the endoscope position; calculating a minimum distance and a maximum distance from data of the first region growing using corresponding distances from the distance map; performing a second region growing on the MPR of the lumen for data outside the first region growing; and performing a 3D rendering of data associated with the first region growing and the second region growing.
- a system for performing a virtual endoscopy comprises: a memory device for storing a program; a processor in communication with the memory device, the processor operative with the program to: calculate a distance map using 3D data of a lumen; calculate an MPR of the lumen, wherein the MPR is calculated orthogonal to the lumen at an endoscope position; perform a first region growing on the MPR of the lumen at the endoscope position; calculate a minimum distance and a maximum distance from data of the first region growing using corresponding distances from the distance map; perform a second region growing on the MPR of the lumen for data outside the first region growing; and perform a 3D rendering of data associated with the first region growing and the second region growing.
- a computer program product comprising a computer useable medium having computer program logic recorded thereon for performing a virtual endoscopy
- the computer program logic comprises: program code for calculating a distance map using 3D data of a lumen; program code for calculating an MPR of the lumen, wherein the MPR is calculated orthogonal to the lumen at an endoscope position; program code for performing a first region growing on the MPR of the lumen at the endoscope position; program code for calculating a minimum distance and a maximum distance from data of the first region growing using corresponding distances from the distance map; program code for performing a second region growing on the MPR of the lumen for data outside the first region growing; and program code for performing a 3D rendering of data associated with the first region growing and the second region growing.
- a system for performing a virtual endoscopy comprises: means for calculating a distance map using 3D data of a lumen; means for calculating an MPR of the lumen, wherein the MPR is calculated orthogonal to the lumen at an endoscope position; means for performing a first region growing on the MPR of the lumen at the endoscope position; means for calculating a minimum distance and a maximum distance from data of the first region growing using corresponding distances from the distance map; means for performing a second region growing on the MPR of the lumen for data outside the first region growing; and means for performing a 3D rendering of data associated with the first region growing and the second region growing.
- a method for performing a virtual endoscopy comprises the steps of: acquiring 3D data from a lumen; calculating a distance map using the 3D data of the lumen; positioning an endoscope at a desired position in the lumen; calculating an MPR of the lumen, wherein the MPR is calculated orthogonal to the lumen at the endoscope position; performing a first region growing on the MPR of the lumen at the endoscope position; marking data associated with the first region growing for rendering; calculating a minimum distance and a maximum distance from the marked data of the first region growing using corresponding distances from the distance map; performing a plurality of region growings for data outside the marked data region that is within a threshold associated with the calculation of the minimum and maximum distances; marking data associated with the plurality of region growings for rendering; and performing a 3D rendering of the marked regions associated with the first growing and the plurality of region growings.
- FIG. 1 is a block diagram of a system for performing a virtual endoscopy according to an exemplary embodiment of the present invention
- FIG. 2 is a flowchart showing an operation of a method for performing a virtual endoscopy according to an exemplary embodiment of the present invention
- FIG. 3 is a three-dimensional (3D) rendering of a lumen according to an exemplary embodiment of the present invention
- FIG. 4 is a lumen that was rendered in 3D that includes a portion that was not rendered in 3D; and FIG. 5 is the portion of the lumen of FIG. 4 that was not rendered in 3D, rendered in 3D, according to an exemplary embodiment of the present invention.
- FIG. 1 is a block diagram of a system 100 for performing a virtual endoscopy according to an exemplary embodiment of the present invention.
- the system 100 includes, inter alia, a scanning device 105, a personal computer (PC) 110 and an operator's console 115 connected over, for example, an Ethernet network 120.
- the scanning device 105 may be a magnetic resonance imaging (MRI) device, a computed tomography (CT) imaging device, a helical CT device, a positron emission tomography (PET) device, a two-dimensional (2D) or three-dimensional (3D) fluoroscopic imaging device, a 2D, 3D, or four-dimensional (4D) ultrasound imaging device, or an x-ray device, etc.
- MRI magnetic resonance imaging
- CT computed tomography
- PET positron emission tomography
- 2D two-dimensional
- 3D three-dimensional
- 4D four-dimensional
- the PC 110 which may be a portable or laptop computer, a personal digital assistant (PDA), etc., includes a central processing unit (CPU) 125 and a memory 130, which are connected to an input 145 and an output 150.
- the memory 130 includes a random access memory (RAM) 135 and a read only memory (ROM) 140.
- the memory 130 can also include a database, disk drive, tape drive, etc., or a combination thereof.
- the RAM 135 functions as a data memory that stores data used during execution of a program in the CPU 125 and is used as a work area.
- the ROM 140 functions as a program memory for storing a program executed in the CPU 125.
- the input 145 is constituted by a keyboard, mouse, etc.
- the output 150 is constituted by a liquid crystal display (LCD), cathode ray tube (CRT) display, printer, etc.
- LCD liquid crystal display
- CRT cathode ray tube
- the operation of the system 100 is controlled from the operator's console 115, which includes a controller 160, for example, a keyboard, and a display 155, for example, a CRT display.
- the operator's console 115 communicates with the PC 110 and the scanning device 105 so that 2D image data collected by the scanning device 105 can be rendered into 3D data by the PC 110 and viewed on the display 155. It is to be understood that the PC 110 can operate and display information provided by the scanning device 105 absent the operator's console 115.
- FIG. 2 is a flowchart showing an operation of a method for performing a virtual endoscopy according to an exemplary embodiment of the present invention.
- 3D data is acquired from a lumen (step 205). This is accomplished by using the scanning device 105, in this example a CT scanner, which is operated at the operator's console 115, to scan a selected lumen thereby generating a series of 2D images associated with the lumen. The 2D images of the lumen are then converted or transformed into a 3D rendered image.
- the scanning device 105 in this example a CT scanner, which is operated at the operator's console 115, to scan a selected lumen thereby generating a series of 2D images associated with the lumen.
- the 2D images of the lumen are then converted or transformed into a 3D rendered image.
- the lumen can be any one of a colon, a pancreas, a bronchi, a larynx, a trachea, a sinus, an ear canal, a blood vessel, a urethra and a bladder or any other inner open space or cavity of a tubular organ.
- a distance map is calculated using the 3D data from the lumen (step 210).
- the distance map is calculated by assigning a first voxel (e.g., seed voxel) of the lumen an initial distance value of "1".
- the voxels adjacent to the first voxel are examined and if they belong to the lumen and have not been previously assigned a distance value, they are assigned a distance value of "2". Subsequently, the voxels adjacent to the voxels assigned a distance value of "2" are assigned a distance value of "3" if they belong to the lumen and have not been previously assigned a distance value.
- a neighbor e.g., an adjacent voxel
- a distance value of "n+1" if it belongs to the lumen and has not been assigned a distance value.
- an endoscope e.g., a virtual endoscope
- a desired location in the lumen is positioned at a desired location in the lumen (step 215). This is accomplished by a user clicking on a screen location associated with an area of the lumen that analysis of is desired or by conducting a flythrough of the lumen via a pre-programmed "flight path" to find a desired location for study.
- a multiplanar reconstruction (MPR) orthogonal to the lumen at the endoscope position is calculated (step 220). Using the MPR image of the lumen, a region growing is then performed at the endoscope position (step 225).
- MPR multiplanar reconstruction
- a seed voxel is selected at for example, the center of the endoscope position and it is assigned a first value. Its neighboring voxels are then read and the neighboring voxels are compared to a threshold range, which may be determined by marking a region of interest in the lumen, to determine if such neighboring voxels (e.g., adjacent voxels) fall within the threshold range. If the voxel or voxels are within the threshold range it/they are assigned a second value and the process is repeated until all voxels in the region of interest have been tested and/or assigned values.
- the data associated with the region growing is then marked as a candidate for 3D rendering (step 230).
- This data is marked by assigning it an identifier, which may be for example, a value different than all other pixel or voxel values in the MPR.
- a user can proceed to perform a 3D rendering of the marked data in step 260 or continue to modify the MPR image in step 240 (step 235). If the user goes to step 260, the MPR data is combined with a 3D rendering of the marked data to provide an enhanced image of the lumen. In other words, the marked pixels or voxels in the MPR are replaced by a 3D rendering of the lumen.
- FIG. 3 An exemplary image 300 resulting from directly proceeding from step 235 to step 260 is shown in FIG. 3.
- information outside the lumen in this example the lumen is a colon
- information outside the wall of the colon is visible and, by using this information, the thickness of the colon's wall can be determined and abnormalities such as a polyp can be observed.
- the surrounding MPR image sections are not rendered (e.g., not clear images of the colon) because they were not marked for rendering.
- the image 300 displays only the desired portion of the lumen selected earlier by the user in step 215.
- step 235 can be removed and the sequence in FIG. 2 would proceed directly to step 240.
- step 240 minimum and maximum distances of the marked data of the first region growing from the distance map are calculated (step 240). This is accomplished by looking up the distance values of all the marked data (e.g., marked pixels or voxels) and tabulating their minimum and maximum distances from their corresponding locations on the distance map of step 210. Once the distance values have been calculated, additional region growings can be performed for data outside the first marked region that is believed to be part of the desired lumen. An example of data that is outside a marked region is illustrated in image 400 of FIG. 4.
- the image 400 includes a portion of a lumen that was not subject to 3D rendering (again, in this example the lumen is a colon).
- An arrow indicates this portion (i.e., a portion of the lumen that was not marked after the first region growing).
- another region growing is performed for data outside the first region growing (step 245). This is accomplished by examining all of the pixels or voxels of the MPR that belong to the lumen that were not marked after the first region growing.
- pixels or voxels are found, and they are within a close proximity to the calculated minimum and maximum distances of the marked data from the first region growing, they will be used as a seed for subsequent region growings (e.g., second, third, etc., region growings). Following this, the data associated with the region growing is marked as a candidate for 3D rendering and assigned an identifier (step 250). This sequence (steps 245-255) will repeat itself until all region growings based on the distance of the seed pixel to the first region growing have been completed (step 255).
- step 245-255 just a single region growing could take place in this sequence (steps 245-255) and that a user could have the option to proceed directly to step 260 after the single region growing. In other words, only a second region growing will be performed during this sequence, not third, fourth, etc., region growings.
- a threshold based on the calculated maximum and minimum distances could be set to limit the area in which the second or subsequent region growings are to be performed.
- the threshold can simply be set to the calculated minimum and maximum distances (therefore the second region growing can not extend beyond these points), it can be set to half the calculated minimum and maximum distances or it can be set to a limit beyond the calculated maximum and minimum distances.
- a 3D rendering is performed on the marked data of the first, second, third, etc., region growings using a 3D rendering technique such as raycasting, surface rendering (e.g., shaded surface rendering), volume rendering, etc.
- a 3D rendering technique such as raycasting, surface rendering (e.g., shaded surface rendering), volume rendering, etc.
- the 3D rendering can be performing using the CPU 125 of FIG. 1 or by dedicated rendering hardware such as a graphics card, volume rendering card, etc.
- the resulting 3D rendering of the marked MPR image is illustrated in image 500 of FIG. 5.
- image 500 the portion of the lumen of FIG. 4 that is indicated by the arrow is now visible. Accordingly, information outside the wall of the colon is visible and information such as the thickness of the colon's wall can be determined and abnormalities such as a polyp can be observed.
- a user can move the endoscope to another position in the lumen and repeat the process described above (step 265).
- the present invention may be implemented in various forms of hardware, software, firmware, special purpose processors, or a combination thereof.
- the present invention may be implemented in software as an application program tangibly embodied on a program storage device.
- the application program may be uploaded to, and executed by, a machine comprising any suitable architecture.
Abstract
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Priority Applications (3)
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DE112004000352T DE112004000352B4 (en) | 2003-03-12 | 2004-03-11 | System and method for performing a virtual endoscopy |
JP2005518895A JP2006519631A (en) | 2003-03-12 | 2004-03-11 | Execution system and execution method for virtual endoscopy |
CN2004800067415A CN1771517B (en) | 2003-03-12 | 2004-03-11 | System and method for performing a virtual endoscopy |
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US45410503P | 2003-03-12 | 2003-03-12 | |
US60/454,105 | 2003-03-12 | ||
US10/795,918 US7304644B2 (en) | 2003-03-12 | 2004-03-08 | System and method for performing a virtual endoscopy |
US10/795,918 | 2004-03-08 |
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WO2004081873A2 true WO2004081873A2 (en) | 2004-09-23 |
WO2004081873A3 WO2004081873A3 (en) | 2005-03-31 |
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US (1) | US7304644B2 (en) |
JP (1) | JP2006519631A (en) |
CN (1) | CN1771517B (en) |
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WO (1) | WO2004081873A2 (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006346177A (en) * | 2005-06-16 | 2006-12-28 | Toshiba Corp | Image diagnostic apparatus, image processor, and three-dimensional image data display method |
DE102006020398A1 (en) * | 2006-04-28 | 2007-10-31 | Siemens Ag | Medical-technical diagnostic system, has processing unit arranged such that representations are simultaneously displayable, where one of representations represents probe detected by diagnostic unit and structures surrounding probe |
WO2016019439A1 (en) * | 2014-08-06 | 2016-02-11 | Commonwealth Scientific And Industrial Research Organisation | Representing an interior of a volume |
Families Citing this family (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE10246355A1 (en) * | 2002-10-04 | 2004-04-15 | Rust, Georg-Friedemann, Dr. | Interactive virtual endoscopy method, requires two representations of three-dimensional data record with computed relative position of marked image zone in one representation |
US7623900B2 (en) | 2005-09-02 | 2009-11-24 | Toshiba Medical Visualization Systems Europe, Ltd. | Method for navigating a virtual camera along a biological object with a lumen |
US20080117210A1 (en) * | 2006-11-22 | 2008-05-22 | Barco N.V. | Virtual endoscopy |
US7853058B2 (en) * | 2006-11-22 | 2010-12-14 | Toshiba Medical Visualization Systems Europe, Limited | Determining a viewpoint for navigating a virtual camera through a biological object with a lumen |
US8840558B2 (en) * | 2008-06-05 | 2014-09-23 | Starkey Laboratories, Inc. | Method and apparatus for mathematically characterizing ear canal geometry |
US20100248200A1 (en) * | 2008-09-26 | 2010-09-30 | Ladak Hanif M | System, Method and Computer Program for Virtual Reality Simulation for Medical Procedure Skills Training |
JP5433240B2 (en) * | 2009-01-21 | 2014-03-05 | 株式会社東芝 | Ultrasonic diagnostic apparatus and image display apparatus |
CN101849843B (en) * | 2009-03-31 | 2013-03-13 | 上海交通大学医学院附属新华医院 | Navigation method of three-dimensional cardiac ultrasonic virtual endoscope |
US9433373B2 (en) * | 2009-06-05 | 2016-09-06 | Starkey Laboratories, Inc. | Method and apparatus for mathematically characterizing ear canal geometry |
US8611989B2 (en) * | 2010-11-30 | 2013-12-17 | Kabushiki Kaisha Toshiba | Multi-planar reconstruction lumen imaging method and apparatus |
CN102078179B (en) * | 2011-01-31 | 2012-05-30 | 广州宝胆医疗器械科技有限公司 | Three-dimensional electronic colonoscope system |
CN104066380B (en) * | 2012-02-01 | 2016-11-09 | 东芝医疗系统株式会社 | Diagnostic ultrasound equipment, image processing apparatus |
JP6006092B2 (en) * | 2012-11-15 | 2016-10-12 | 東芝メディカルシステムズ株式会社 | Ultrasonic diagnostic apparatus, image processing apparatus, and program |
CN103968829B (en) * | 2014-05-13 | 2016-12-07 | 清华大学 | Three-dimensional fix method for tracing based on virtual signage thing and system |
US10242488B1 (en) * | 2015-03-02 | 2019-03-26 | Kentucky Imaging Technologies, LLC | One-sided transparency: a novel visualization for tubular objects |
KR101717371B1 (en) * | 2015-08-31 | 2017-03-16 | 왕용진 | 2-dimentional scanning videokymography creation method using real-time or pre-stored ultra high speed laryngeal endoscopy video, 2-dimentional scanning videokymography creation server performing the same, and storage medium storing the same |
CN106890031B (en) * | 2017-04-11 | 2020-05-05 | 东北大学 | Marker identification and marking point positioning method and operation navigation system |
CN111212724B (en) * | 2017-10-14 | 2022-06-17 | 惠普发展公司,有限责任合伙企业 | Processing 3D object models |
US10510178B2 (en) | 2018-02-27 | 2019-12-17 | Verizon Patent And Licensing Inc. | Methods and systems for volumetric reconstruction based on a confidence field |
CN108461128A (en) * | 2018-03-02 | 2018-08-28 | 上海联影医疗科技有限公司 | Medical image processing method and system and image processing terminal |
US11132830B2 (en) * | 2018-03-29 | 2021-09-28 | Biosense Webster (Israel) Ltd. | Static virtual camera positioning |
US11151789B1 (en) | 2019-03-25 | 2021-10-19 | Kentucky Imaging Technologies | Fly-in visualization for virtual colonoscopy |
US11521316B1 (en) | 2019-04-03 | 2022-12-06 | Kentucky Imaging Technologies | Automatic extraction of interdental gingiva regions |
US11044400B1 (en) | 2019-04-03 | 2021-06-22 | Kentucky Imaging Technologies | Frame stitching in human oral cavity environment using intraoral camera |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5734384A (en) * | 1991-11-29 | 1998-03-31 | Picker International, Inc. | Cross-referenced sectioning and reprojection of diagnostic image volumes |
Family Cites Families (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4945478A (en) * | 1987-11-06 | 1990-07-31 | Center For Innovative Technology | Noninvasive medical imaging system and method for the identification and 3-D display of atherosclerosis and the like |
US5920319A (en) * | 1994-10-27 | 1999-07-06 | Wake Forest University | Automatic analysis in virtual endoscopy |
US5782762A (en) * | 1994-10-27 | 1998-07-21 | Wake Forest University | Method and system for producing interactive, three-dimensional renderings of selected body organs having hollow lumens to enable simulated movement through the lumen |
US5611025A (en) * | 1994-11-23 | 1997-03-11 | General Electric Company | Virtual internal cavity inspection system |
US6167296A (en) * | 1996-06-28 | 2000-12-26 | The Board Of Trustees Of The Leland Stanford Junior University | Method for volumetric image navigation |
US6331116B1 (en) * | 1996-09-16 | 2001-12-18 | The Research Foundation Of State University Of New York | System and method for performing a three-dimensional virtual segmentation and examination |
US7194117B2 (en) * | 1999-06-29 | 2007-03-20 | The Research Foundation Of State University Of New York | System and method for performing a three-dimensional virtual examination of objects, such as internal organs |
US5891030A (en) * | 1997-01-24 | 1999-04-06 | Mayo Foundation For Medical Education And Research | System for two dimensional and three dimensional imaging of tubular structures in the human body |
US6346940B1 (en) * | 1997-02-27 | 2002-02-12 | Kabushiki Kaisha Toshiba | Virtualized endoscope system |
US6246784B1 (en) * | 1997-08-19 | 2001-06-12 | The United States Of America As Represented By The Department Of Health And Human Services | Method for segmenting medical images and detecting surface anomalies in anatomical structures |
US6674894B1 (en) * | 1999-04-20 | 2004-01-06 | University Of Utah Research Foundation | Method and apparatus for enhancing an image using data optimization and segmentation |
US20020009215A1 (en) * | 2000-01-18 | 2002-01-24 | Arch Development Corporation | Automated method and system for the segmentation of lung regions in computed tomography scans |
US6898303B2 (en) * | 2000-01-18 | 2005-05-24 | Arch Development Corporation | Method, system and computer readable medium for the two-dimensional and three-dimensional detection of lesions in computed tomography scans |
US7274810B2 (en) * | 2000-04-11 | 2007-09-25 | Cornell Research Foundation, Inc. | System and method for three-dimensional image rendering and analysis |
JP2004518186A (en) * | 2000-10-02 | 2004-06-17 | ザ リサーチ ファウンデーション オブ ステイト ユニヴァーシティ オブ ニューヨーク | Centerline and tree branch selection decision for virtual space |
US7072501B2 (en) * | 2000-11-22 | 2006-07-04 | R2 Technology, Inc. | Graphical user interface for display of anatomical information |
KR100788643B1 (en) * | 2001-01-09 | 2007-12-26 | 삼성전자주식회사 | Searching method of image based on combination of color and texture |
US6816607B2 (en) * | 2001-05-16 | 2004-11-09 | Siemens Corporate Research, Inc. | System for modeling static and dynamic three dimensional anatomical structures by 3-D models |
AU2002341671A1 (en) * | 2001-09-14 | 2003-04-01 | Cornell Research Foundation, Inc. | System, method and apparatus for small pulmonary nodule computer aided diagnosis from computed tomography scans |
WO2003045222A2 (en) * | 2001-11-21 | 2003-06-05 | Viatronix Incorporated | System and method for visualization and navigation of three-dimensional medical images |
US7397937B2 (en) * | 2001-11-23 | 2008-07-08 | R2 Technology, Inc. | Region growing in anatomical images |
DE10160206A1 (en) * | 2001-12-07 | 2003-06-18 | Philips Intellectual Property | Method and device for creating an isolated representation of body structures |
US7123766B2 (en) * | 2002-02-11 | 2006-10-17 | Cedara Software Corp. | Method and system for recognizing and selecting a region of interest in an image |
US6574304B1 (en) * | 2002-09-13 | 2003-06-03 | Ge Medical Systems Global Technology Company, Llc | Computer aided acquisition of medical images |
US7260250B2 (en) * | 2002-09-30 | 2007-08-21 | The United States Of America As Represented By The Secretary Of The Department Of Health And Human Services | Computer-aided classification of anomalies in anatomical structures |
US7123760B2 (en) * | 2002-11-21 | 2006-10-17 | General Electric Company | Method and apparatus for removing obstructing structures in CT imaging |
EP1455307A1 (en) * | 2003-03-06 | 2004-09-08 | MeVis GmbH | Partial volume visualization |
US7142726B2 (en) * | 2003-03-19 | 2006-11-28 | Mitsubishi Electric Research Labs, Inc. | Three-dimensional scene reconstruction from labeled two-dimensional images |
WO2005010699A2 (en) * | 2003-07-15 | 2005-02-03 | Medical Metrx Solutions, Inc. | Generating a computer model using scan data of a patient |
US7209581B2 (en) * | 2003-07-31 | 2007-04-24 | Siemens Medical Solutions Usa, Inc. | System and method for ground glass nodule (GGN) segmentation |
-
2004
- 2004-03-08 US US10/795,918 patent/US7304644B2/en not_active Expired - Fee Related
- 2004-03-11 WO PCT/US2004/007300 patent/WO2004081873A2/en active Search and Examination
- 2004-03-11 DE DE112004000352T patent/DE112004000352B4/en not_active Expired - Fee Related
- 2004-03-11 CN CN2004800067415A patent/CN1771517B/en not_active Expired - Fee Related
- 2004-03-11 JP JP2005518895A patent/JP2006519631A/en not_active Withdrawn
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5734384A (en) * | 1991-11-29 | 1998-03-31 | Picker International, Inc. | Cross-referenced sectioning and reprojection of diagnostic image volumes |
Non-Patent Citations (1)
Title |
---|
WYATT C L ET AL: "AUTOMATIC SEGMENTATION OF THE COLON FOR VIRTUAL COLONOSCOPY" COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, PERGAMON PRESS, NEW YORK, NY, US, vol. 24, no. 1, 2000, pages 1-9, XP000925199 ISSN: 0895-6111 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006346177A (en) * | 2005-06-16 | 2006-12-28 | Toshiba Corp | Image diagnostic apparatus, image processor, and three-dimensional image data display method |
DE102006020398A1 (en) * | 2006-04-28 | 2007-10-31 | Siemens Ag | Medical-technical diagnostic system, has processing unit arranged such that representations are simultaneously displayable, where one of representations represents probe detected by diagnostic unit and structures surrounding probe |
DE102006020398B4 (en) * | 2006-04-28 | 2015-09-03 | Siemens Aktiengesellschaft | Medical technical diagnostic system |
WO2016019439A1 (en) * | 2014-08-06 | 2016-02-11 | Commonwealth Scientific And Industrial Research Organisation | Representing an interior of a volume |
US10424062B2 (en) | 2014-08-06 | 2019-09-24 | Commonwealth Scientific And Industrial Research Organisation | Representing an interior of a volume |
Also Published As
Publication number | Publication date |
---|---|
DE112004000352B4 (en) | 2013-09-12 |
US20040202990A1 (en) | 2004-10-14 |
US7304644B2 (en) | 2007-12-04 |
JP2006519631A (en) | 2006-08-31 |
DE112004000352T5 (en) | 2006-03-09 |
WO2004081873A3 (en) | 2005-03-31 |
CN1771517A (en) | 2006-05-10 |
CN1771517B (en) | 2010-05-26 |
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