+

WO2006028965A9 - Systeme et procede de segmentation d'une structure etudiee a l'aide d'une interpolation d'une surface de separation dans une zone de fixation a une structure presentant des proprietes similaires - Google Patents

Systeme et procede de segmentation d'une structure etudiee a l'aide d'une interpolation d'une surface de separation dans une zone de fixation a une structure presentant des proprietes similaires

Info

Publication number
WO2006028965A9
WO2006028965A9 PCT/US2005/031321 US2005031321W WO2006028965A9 WO 2006028965 A9 WO2006028965 A9 WO 2006028965A9 US 2005031321 W US2005031321 W US 2005031321W WO 2006028965 A9 WO2006028965 A9 WO 2006028965A9
Authority
WO
WIPO (PCT)
Prior art keywords
interest
border
transformed
demarcation
interpolating
Prior art date
Application number
PCT/US2005/031321
Other languages
English (en)
Other versions
WO2006028965A3 (fr
WO2006028965A2 (fr
Inventor
Anna Jerebko
Luca Bogoni
Sarang Lakare
Original Assignee
Anna Jerebko
Luca Bogoni
Sarang Lakare
Siemens Medical Solutions
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Anna Jerebko, Luca Bogoni, Sarang Lakare, Siemens Medical Solutions filed Critical Anna Jerebko
Publication of WO2006028965A2 publication Critical patent/WO2006028965A2/fr
Publication of WO2006028965A3 publication Critical patent/WO2006028965A3/fr
Publication of WO2006028965A9 publication Critical patent/WO2006028965A9/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/181—Segmentation; Edge detection involving edge growing; involving edge linking
    • 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
    • G06T2207/30032—Colon polyp
    • 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
    • G06T2207/30064—Lung nodule

Definitions

  • the present invention relates to image segmentation, and more particularly, to a system and method for segmenting a structure of interest by using an interpolation of a separating surface in an area of attachment to a structure having similar properties.
  • CAD computer-aided detection and diagnosis
  • CT computed tomography
  • CAD techniques such as computed tomography (CT) colonography can locate and identify polyps on the colon wall by using geometric features of the colon surface and/or volumetric properties near the surface to assist with detection.
  • CT computed tomography
  • Recently, such techniques have been enhanced to segment polyps to provide the entire voxel set of the polyp. This data can then be used to quantify certain characteristics of the polyp.
  • CAD techniques such as virtual endoscopy based on two-dimensional (2D) and three-dimensional (3D) analysis of image data acquired during diagnostic CT scans can be used locate and identify lung nodules or aneurisms by using geometric features and/or volumetric properties of the lung and its vessel trees. Similar to CT colonoscopy, virtual bronchoscopy and lung nodule detection in chest CT scans includes advanced segmentation methods to provide a medical practitioner with information regarding detected thoracic and lung nodules. This data could then be used to quantify certain characteristics of the nodules and aid in the diagnosis of diseases associated therewith.
  • CAD 1 the surface or boundary between, for example, a segmented polyp and a colon or bronchi lumen or between a lung nodule and the air inside the lungs is relatively easy to determine due to the large intensity discrepancy between these regions.
  • the boundaries between polyp tissues of similar intensity are not very obvious.
  • a polyp 110 is always connected to another object having a similar intensity such as a colon fold 120 or colon wall 130 as shown in FIG. 1.
  • special image-processing techniques need to be applied to successfully locate and separate them.
  • a hysteresis thresholding is performed that uses some colonic volumetric features. This technique first locates voxels with low curvedness values and high shape indexes and then clusters them to segment the polyp. This technique, however, does not sufficiently identify small polyps and flat polyps since there is an insufficient number of voxels with low curvedness values and high shape indexes for clustering.
  • Canny edge detectors are used to locate the polyp-lumen boundary and Radon transformation is used to identify round shaped polyps. This technique, however, does not robustly segment all polyp types.
  • the present invention overcomes the foregoing and other problems encountered in the known teachings by providing a system and method for segmenting a structure of interest by using an interpolation of a separating surface in an area of attachment to a structure having similar properties.
  • a method for segmenting a structure of interest comprises: segmenting a surface of the structure of interest; and interpolating a border of the structure of interest, wherein the border separates the structure of interest from other structures having similar properties.
  • the structure of interest is one of a polyp, lung nodule, bronchi lesion or pulmonary emboli.
  • the step of interpolating comprises: transforming a portion of the border of the structure of interest where there is a demarcation into a transformed coordinate space; selecting a coordinate space for interpolation in view of salient properties of the structure of interest; interpolating the portion of the border of the structure of interest where there is no demarcation in the transformed coordinate space; and mapping the interpolated portion of the border of the structure of interest where there is no demarcation back to an original coordinate space of the structure of interest.
  • the original coordinate space is Cartesian.
  • the surface of the structure of interest is transformed into spherical or ellipsoidal coordinates.
  • the surface of the structure of interest is transformed by using a center mass of the structure of interest as the origin for the transformation.
  • the step of interpolating comprises: computing a normalization factor to obtain a continuous representation of the surface of the structure of interest in a transformed space; and determining coordinates of voxels in a portion of the border of the structure of interest that has no demarcation by using locations of the voxels surrounding the portion of the border of the structure of interest that has no demarcation in the transformed space.
  • an interpolation method for separating surfaces of an anatomical structure comprises: segmenting a surface of the anatomical structure; and interpolating a border of the anatomical structure, wherein the border separates the anatomical structure from other structures having similar properties, wherein the step of interpolating the border, comprises: transforming a portion of the border of the anatomical structure where there is a demarcation into a transformed coordinate space; computing a normalization factor to obtain a continuous representation of the surface of the anatomical structure in the transformed space; and determining coordinates of voxels in a portion of the border of the anatomical structure that has no demarcation by using locations of the voxels surrounding the portion of the border of the anatomical structure that has no demarcation in the transformed space.
  • the surface of the anatomical structure is transformed into spherical or ellipsoidal coordinates.
  • the surface of the anatomical structure is transformed by using a center mass of the region of interest as the origin for the transformation.
  • the anatomical structure is one of a polyp, lung nodule, bronchi lesion or pulmonary emboli.
  • a system for segmenting a structure of interest comprises: a memory device for storing a program; a processor in communication with the memory device, the processor operative with the program to: segment a surface of the structure of interest; and interpolate a border of the structure of interest, wherein the border separates the structure of interest from other structures having similar properties.
  • the structure of interest is one of a polyp, lung nodule, bronchi lesion or pulmonary emboli.
  • the processor is further operative with the program code when interpolating to: transform a portion of the border of the structure of interest where there is a demarcation into a transformed coordinate space; select a coordinate space for interpolation in view of salient properties of the structure of interest; interpolate the portion of the border of the structure of interest where there is no demarcation in the transformed coordinate space; and map the interpolated portion of the border of the structure of interest where there is no demarcation back to an original coordinate space of the structure of interest.
  • the original coordinate space is Cartesian.
  • the surface of the structure of interest is transformed into spherical or ellipsoidal coordinates.
  • the surface of the structure of interest is transformed by using a center mass of the structure of interest as the origin for the transformation.
  • the processor is further operative with the program code during the step of interpolating to: compute a normalization factor to obtain a continuous representation of the surface of the structure of interest in a transformed space; and determine coordinates of voxels in a portion of the border of the structure of interest that has no demarcation by using locations of the voxels surrounding the portion of the border of the structure of interest that has no demarcation in the transformed space.
  • the structure of interest is acquired by using one of a computed tomography or magnetic resonance imaging device.
  • FIG. 1 is an image of a portion of a colon wall with a protruding polypoid lesion
  • FIG. 2 is a block diagram of a system for segmenting a structure of interest according to an exemplary embodiment of the present invention
  • FIG. 3 is a flowchart illustrating a method for segmenting a structure of interest according to an exemplary embodiment of the present invention
  • FIG. 4 is a flowchart illustrating an interpolating method for segmenting a structure of interest according to an exemplary embodiment of the present invention
  • FIG. 5 is a pair of graphs illustrating the calculation of a normalization factor according to an exemplary embodiment of the present invention
  • FIG. 6 is a pair of graphs illustrating the transformation of a polyp surface to spherical coordinates according to an exemplary embodiment of the present invention
  • FIG. 7 is a sketch illustrating a separating surface for interpolation according to an exemplary embodiment of the present invention.
  • FIG. 8 is a pair of graphs illustrating results of applying an interpolated separating surface to a mapping of FIG. 6;
  • FIG. 9 is a pair of graphs illustrating interpolation results in spherical coordinates according to an exemplary embodiment of the present invention.
  • FIG. 10 is a graphical interface illustrating interpolation results mapped to Cartesian coordinates according to an exemplary embodiment of the present invention.
  • FIG. 2 is a block diagram of a system 200 for segmenting a structure of interest by using an interpolation of a separating surface in an area of attachment to a structure having similar properties according to an exemplary embodiment of the present invention.
  • the system 200 includes, inter alia, a scanning device 205, a personal computer (PC) 210 and an operator's console 215 connected over, for example, an Ethernet network 220.
  • PC personal computer
  • the scanning device 205 may be a magnetic resonance (MR) imaging device, a CT imaging device, a helical CT device, a positron emission tomography (PET) device, a 2D or 3D fluoroscopic imaging device, a 2D, 3D, or four-dimensional (4D) ultrasound imaging device, x-ray device or a hybrid-imaging device capable of CT, MR or other imaging techniques.
  • MR magnetic resonance
  • CT CT
  • PET positron emission tomography
  • 4D four-dimensional
  • the PC 210 which may be a portable or laptop computer, a workstation, etc., includes a central processing unit (CPU) 225 and a memory 230, which are connected to an input 250 and an output 255.
  • the CPU 225 includes a segmentation module 245 that includes one or more methods for segmenting a structure of interest by using an interpolation of a separating surface in an area of attachment to a structure having similar properties.
  • the memory 230 includes a random access memory (RAM) 235 and a read only memory (ROM) 240.
  • the memory 230 can also include a database, disk drive, tape drive, etc., or a combination thereof.
  • the RAM 235 functions as a data memory that stores data used during execution of a program in the CPU 225 and is used as a work area.
  • the ROM 240 functions as a program memory for storing a program executed in the CPU 225.
  • the input 250 is constituted by a keyboard, mouse, etc.
  • the output 255 is constituted by a liquid crystal display (LCD), cathode ray tube (CRT) display, or printer.
  • LCD liquid crystal display
  • CRT cathode ray tube
  • the operation of the system 200 is controlled from the operator's console 215, which includes a controller 265, for example, a keyboard, and a display 260, for example, a CRT display.
  • the operator's console 215 communicates with the PC 210 and the scanning device 205 so that 2D image data collected by the scanning device 205 can be rendered into 3D data by the PC 210 and viewed on the display 260.
  • the PC 210 can be configured to operate and display information provided by the scanning device 205 absent the operator's console 215, using, for example, the input 250 and output 255 devices to execute certain tasks performed by the controller 265 and display 260.
  • the operator's console 215 further includes any suitable image rendering system/tool/application that can process digital image data of an acquired image dataset (or portion thereof) to generate and display 2D, 3D or N-dimensional (ND) (where N is an integer greater than 3) images on the display 260.
  • the image rendering system may be an application that provides 2D/3D/ND rendering and visualization of medical image data, and which executes on a general purpose or specific computer workstation.
  • the image rendering system may enable a user to navigate through a 3D image or a plurality of 2D image slices.
  • the PC 210 may also include an image rendering system/tool/application for processing digital image data of an acquired image dataset to generate and display 2D, 3D or ND images.
  • the segmentation module 245 may also be used by the PC 210 to receive and process digital medical image data, which as noted above, may be in the form of raw image data, 2D reconstructed data (e.g., axial slices), 3D or ND reconstructed data such as volumetric image data or multiplanar reformats, or any combination of such formats.
  • the data processing results can be output from the PC 210 via the network 220 to an image rendering system in the operator's console 215 for generating 2D, 3D or ND renderings of image data in accordance with the data processing results, such as segmentation of organs or anatomical structures, color or intensity variations, and so forth.
  • FIG. 3 is a flowchart showing an operation of a method for segmenting a structure of interest by using an interpolation of a separating surface in an area of attachment to a structure having similar properties according to an exemplary embodiment of the present invention.
  • image data is acquired from, for example, a colon inside a patient (310). This is accomplished by using the scanning device 205, in this example a CT scanner, which is operated at the operator's console 215, to scan the patient's abdomen thereby generating a series of 2D image slices associated with the colon. The 2D image slices of the colon are then combined to form a 3D image 100 as shown, for example, in FIG. 1.
  • the image data could be acquired to observe a variety of organs or blood vessels within a patient.
  • the image data could be acquired by taking x-rays of a patient's lung or by taking a CT scan of a patient's leg or entire body.
  • the image data could be non-medical image data acquired from, for example, non-anatomical structures.
  • the 2D image slices may be combined to form an ND image for analysis in accordance with the present invention.
  • a region or structure of interest such as polyp in the colon is segmented (320).
  • the well defined surface of the region of interest is segmented using, for example, a Canny edge detection technique.
  • segmentation techniques such as snakes or deformable models can be used in this step.
  • a portion of the region of interest where there is no clear demarcation of a border separating it from other parts of the colon is segmented by performing an interpolation according to an exemplary embodiment of the present invention (330). The interpolating process is discussed hereinafter with reference to FIG. 4.
  • FIG. 4 is a flowchart illustrating a method for interpolating a separating surface in an area of attachment to a structure having similar properties according to an exemplary embodiment of the present invention.
  • the local structure has properties such that it is similar to that of, for example, a polyp or lung nodule coupled thereto, thus resulting in no clear demarcation of a border therebetween.
  • a spherical coordinate transformation is performed on a region of interest such as a polyp (410). This is accomplished by transforming the surface of the polyp to spherical coordinates by using the center mass of the polyp surface as the origin for the transformation.
  • the new coordinates r ( ⁇ , ⁇ ) of every point (x,y,z) on the 3D image of the separating surface or edge are calculated as follows:
  • a normalization or stretching factor is computed for each discrete radius r (420).
  • the normalization factor allows portions of the surface, which are at varying distances from the centroid of the spherical transformation, to have a uniform representation in a spherical space.
  • the stretching factor is computed as shown in FIG. 5.
  • the normalization factor e.g., ⁇ (r)
  • ⁇ (r) is calculated as follows:
  • a gap represented by dashed lines 710a,b of an image r ( ⁇ , ⁇ ) corresponds to the base of a polyp 720 that separates the polyp 720 from nearby or surrounding structures such as a colon wall 730.
  • neighboring voxels in the vertical and horizontal directions are determined (430). For example, for each empty voxel, two of its closest neighbors are determined from existing surface patches, first in the vertical ( ⁇ ) and then in the horizontal ( ⁇ ) directions.
  • FIG. 6 illustrates a scenario where for a fixed value ⁇ , two corresponding angles Ti and T 2 are shown as closest neighbors across a region that has no previously computed surface. It is to be understood that empty voxels are indicated, for example, in Cartesian coordinates by the dashed lines 710a,b in FIG. 7 and in the spherical coordinates by darker regions 610a,b in FIG. 6.
  • a section for interpolating between neighbors is determined (440).
  • two sections between, for example, four voxel neighbors having fixed values of ⁇ and ⁇ are determined and triangular relationships between each pair of neighbors, the center of coordinates and radius of the point being interpolated are determined.
  • two of the four voxel neighbors indicated by the tips of the arrows projecting from the center point O which is the center of the coordinates, form a triangle where two sides (e.g., radii ⁇ and r 2 ) and the angle between them cpo are known.
  • the interpolation along both the vertical and horizontal directions for each empty point, indicated by the dashed line 710a,b, in the spherical coordinate system is computed (450).
  • all points lying along the dashed line segment 710a connecting the two voxel neighbors having endpoints of radii ri and r 2 are interpolated.
  • the interpolation can then be performed by spanning the angle ⁇ 0 by the increments ⁇ . From this, each interpolating radius value spanning the linear segment can be computed.
  • the interpolated linear segment in spherical space will span an arc in Cartesian space.
  • Images (a) and (b) of FIG. 8 illustrate the results of applying the interpolation procedure to the mapping shown in FIG. 6 separately for ⁇ and ⁇ pairs.
  • Images (a) and (b) of FIG. 9 illustrate the interpolation results for the polyp base and surface gaps in the spherical coordinates obtained as the average of the radius values obtained by solving the ⁇ and ⁇ triangle depicted in images (a) and (b) of FIG. 8.
  • the interpolating results are integrated (460). This is accomplished by determining final values of radii in empty points of the spanning section by taking an average of the interpolating radii in the vertical and horizontal directions. It is to be understood that straight lines in Cartesian space become concave arcs in spherical space as illustrated by the results of the combination of values shown in images (a) and (b) of FIG. 9. It should also be understood that while the average is being used as a means to interpolate the radius, this could be performed by using a function other than the average to determine a radial contribution, thus enabling different types of interpolating surfaces to be obtained.
  • FIG. 10 Images (a), (b) and (c) of FIG. 10 illustrate three orthogonal views of the same polyp surface shown in FIG. 1 with the segmentation results highlighted.
  • a structure of interest can be segmented by interpolating a separating surface in an area of attachment to a local structure having similar properties.
  • This technique can be implemented as an extension or alternative to CAD methods such as virtual colonoscopy or bronchoscopy or other automated polyp, lung nodule or aneurism visualization and detection methods.
  • CAD methods such as virtual colonoscopy or bronchoscopy or other automated polyp, lung nodule or aneurism visualization and detection methods.
  • this technique could be used alone or in combination with CAD methods to obtain additional discriminative features for characterization of abnormal lesions or as inputs for classification procedures.
  • 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 (e.g., magnetic floppy disk, RAM, CD ROM, DVD, ROM, and flash memory).
  • the application program may be uploaded to, and executed by, a machine comprising any suitable architecture.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Image Analysis (AREA)

Abstract

L'invention concerne un système et un procédé de segmentation d'une structure étudiée. Le procédé consiste à segmenter une surface de la structure à étudier (320) et à interpoler une frontière de la structure étudiée. La frontière séparant la structure étudiée d'autres structures ayant des propriétés similaires (330).
PCT/US2005/031321 2004-09-07 2005-09-02 Systeme et procede de segmentation d'une structure etudiee a l'aide d'une interpolation d'une surface de separation dans une zone de fixation a une structure presentant des proprietes similaires WO2006028965A2 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US60756504P 2004-09-07 2004-09-07
US60/607,565 2004-09-07
US11/207,318 2005-08-19
US11/207,318 US7492968B2 (en) 2004-09-07 2005-08-19 System and method for segmenting a structure of interest using an interpolation of a separating surface in an area of attachment to a structure having similar properties

Publications (3)

Publication Number Publication Date
WO2006028965A2 WO2006028965A2 (fr) 2006-03-16
WO2006028965A3 WO2006028965A3 (fr) 2006-04-13
WO2006028965A9 true WO2006028965A9 (fr) 2006-05-11

Family

ID=35996288

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2005/031321 WO2006028965A2 (fr) 2004-09-07 2005-09-02 Systeme et procede de segmentation d'une structure etudiee a l'aide d'une interpolation d'une surface de separation dans une zone de fixation a une structure presentant des proprietes similaires

Country Status (2)

Country Link
US (1) US7492968B2 (fr)
WO (1) WO2006028965A2 (fr)

Families Citing this family (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050152588A1 (en) * 2003-10-28 2005-07-14 University Of Chicago Method for virtual endoscopic visualization of the colon by shape-scale signatures, centerlining, and computerized detection of masses
JP4855868B2 (ja) * 2006-08-24 2012-01-18 オリンパスメディカルシステムズ株式会社 医療用画像処理装置
US8165376B2 (en) * 2006-12-11 2012-04-24 Siemens Corporation System and method for automatic detection of rib metastasis in computed tomography volume
US8184888B2 (en) * 2007-09-19 2012-05-22 Siemens Medical Solutions Usa, Inc. Method and system for polyp segmentation for 3D computed tomography colonography
US8126244B2 (en) * 2007-09-21 2012-02-28 Siemens Medical Solutions Usa, Inc. User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography
US8073217B2 (en) * 2007-11-01 2011-12-06 Siemens Medical Solutions Usa, Inc. Structure segmentation via MAR-cut
US8189886B2 (en) * 2008-08-13 2012-05-29 Carestream Health, Inc. Method for detecting anatomical structures
US8577108B2 (en) 2008-08-13 2013-11-05 Carestream Health, Inc. Method for detecting anatomical structures
US8675933B2 (en) 2010-04-30 2014-03-18 Vucomp, Inc. Breast segmentation in radiographic images
US9262822B2 (en) 2010-04-30 2016-02-16 Vucomp, Inc. Malignant mass detection and classification in radiographic images
WO2012006318A1 (fr) 2010-07-07 2012-01-12 Vucomp, Inc. Système de marquage pour détection assistée par ordinateur d'anomalies du sein
WO2014117108A1 (fr) * 2013-01-25 2014-07-31 Duke University Segmentation et identification d'éléments à contour fermé dans des images en utilisant la théorie des graphes et la transformée quasi-polaire
GB2529671B (en) * 2014-08-28 2017-03-08 Canon Kk Transformation of 3-D object for object segmentation in 3-D medical image
WO2016127140A1 (fr) 2015-02-05 2016-08-11 Duke University Configurations de télescope compactes pour des systèmes de balayage de lumière et leurs procédés d'utilisation
WO2016127088A1 (fr) 2015-02-06 2016-08-11 Duke University Systèmes et procédés d'affichage stéréoscopique pour afficher des données et des informations chirurgicales dans un microscope chirurgical
US10694939B2 (en) 2016-04-29 2020-06-30 Duke University Whole eye optical coherence tomography(OCT) imaging systems and related methods
US12062183B2 (en) 2019-03-29 2024-08-13 Howmedica Osteonics Corp. Closed surface fitting for segmentation of orthopedic medical image data

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1058131B1 (fr) * 1999-06-03 2004-09-01 Jason Geosystems B.V. Procédé de détermination de changements spatiaux dans la stratigraphie de la structure sous-sol, de la lithologie et de la teneur fluide et réduction du bruit sismique
US6577752B2 (en) 2001-06-15 2003-06-10 Arch Development Corporation Automated method and system for the delineation of the chest wall in computed tomography scans for the assessment of pleural disease
US20030036083A1 (en) * 2001-07-19 2003-02-20 Jose Tamez-Pena System and method for quantifying tissue structures and their change over time
US20030072479A1 (en) * 2001-09-17 2003-04-17 Virtualscopics System and method for quantitative assessment of cancers and their change over time
US7136518B2 (en) * 2003-04-18 2006-11-14 Medispectra, Inc. Methods and apparatus for displaying diagnostic data
US6765983B2 (en) * 2002-12-13 2004-07-20 General Electric Company Method and apparatus for imaging a region of dynamic tissue
US20040147830A1 (en) * 2003-01-29 2004-07-29 Virtualscopics Method and system for use of biomarkers in diagnostic imaging
US7333644B2 (en) 2003-03-11 2008-02-19 Siemens Medical Solutions Usa, Inc. Systems and methods for providing automatic 3D lesion segmentation and measurements
US20050152588A1 (en) * 2003-10-28 2005-07-14 University Of Chicago Method for virtual endoscopic visualization of the colon by shape-scale signatures, centerlining, and computerized detection of masses

Also Published As

Publication number Publication date
US7492968B2 (en) 2009-02-17
US20060050991A1 (en) 2006-03-09
WO2006028965A3 (fr) 2006-04-13
WO2006028965A2 (fr) 2006-03-16

Similar Documents

Publication Publication Date Title
CN112529834B (zh) 病理图像模式在3d图像数据中的空间分布
US7333644B2 (en) Systems and methods for providing automatic 3D lesion segmentation and measurements
EP2572332B1 (fr) Visualisation de données d'image médicale à amélioration localisée
US7336809B2 (en) Segmentation in medical images
JP6877868B2 (ja) 画像処理装置、画像処理方法および画像処理プログラム
US7840051B2 (en) Medical image segmentation
US7492968B2 (en) System and method for segmenting a structure of interest using an interpolation of a separating surface in an area of attachment to a structure having similar properties
JP6918528B2 (ja) 医用画像処理装置及び医用画像処理プログラム
US20030099390A1 (en) Lung field segmentation from CT thoracic images
JP2008510499A (ja) 解剖学的可視化／測定システム
US9129391B2 (en) Semi-automated preoperative resection planning
US8520923B2 (en) Reporting organ volume for a medical digital image
EP2601637B1 (fr) Système et procédé de segmentation multi-modalité d'un tissu interne avec rétroaction en direct
US7391893B2 (en) System and method for the detection of shapes in images
US7684602B2 (en) Method and system for local visualization for tubular structures
US8515200B2 (en) System, software arrangement and method for segmenting an image
JP4473578B2 (ja) 体の構造の孤立した視覚化されたものを形成する方法及び装置
WO2006023152A1 (fr) Systeme et procede d'extraction d'une paroi du colon en presence de selles marquees ou de zones affaissees du colon
US8712119B2 (en) Systems and methods for computer-aided fold detection
WO2006055031A2 (fr) Procede et systeme de visualisation locale pour des structures tubulaires
CN100339872C (zh) 提供自动三维损害分割和测量的系统及方法
WO2005013197A1 (fr) Systeme et procede de segmentation d'un nodule en verre depoli
WO2005002432A2 (fr) Systeme et procede pour la visualisation de polypes

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A2

Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BW BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE EG ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KM KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NA NG NI NO NZ OM PG PH PL PT RO RU SC SD SE SG SK SL SM SY TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW

AL Designated countries for regional patents

Kind code of ref document: A2

Designated state(s): BW GH GM KE LS MW MZ NA SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LT LU LV MC NL PL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG

COP Corrected version of pamphlet

Free format text: PAGES 1/10-10/10, DRAWINGS, REPLACED BY NEW PAGES 1/10-10/10; DUE TO LATE TRANSMITTAL BY THE RECEIVING OFFICE

121 Ep: the epo has been informed by wipo that ep was designated in this application
NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 05794720

Country of ref document: EP

Kind code of ref document: A2

点击 这是indexloc提供的php浏览器服务，不要输入任何密码和下载