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WO2013038284A1 - Génération d'un modèle tridimensionnel d'un objet d'intérêt - Google Patents

Génération d'un modèle tridimensionnel d'un objet d'intérêt Download PDF

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Publication number
WO2013038284A1
WO2013038284A1 PCT/IB2012/054368 IB2012054368W WO2013038284A1 WO 2013038284 A1 WO2013038284 A1 WO 2013038284A1 IB 2012054368 W IB2012054368 W IB 2012054368W WO 2013038284 A1 WO2013038284 A1 WO 2013038284A1
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WO
WIPO (PCT)
Prior art keywords
model
image data
ray image
data
dimensional
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Application number
PCT/IB2012/054368
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English (en)
Inventor
Klaus Erhard
Michael Grass
Tim Nielsen
Thomas Buelow
Original Assignee
Koninklijke Philips Electronics N.V.
Philips Intellectual Property & Standards Gmbh
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Filing date
Publication date
Application filed by Koninklijke Philips Electronics N.V., Philips Intellectual Property & Standards Gmbh filed Critical Koninklijke Philips Electronics N.V.
Publication of WO2013038284A1 publication Critical patent/WO2013038284A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0073—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by tomography, i.e. reconstruction of 3D images from 2D projections
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room
    • A61B5/0035—Features or image-related aspects of imaging apparatus, e.g. for MRI, optical tomography or impedance tomography apparatus; Arrangements of imaging apparatus in a room adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A61B5/0091—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for mammography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/44—Constructional features of apparatus for radiation diagnosis
    • A61B6/4417—Constructional features of apparatus for radiation diagnosis related to combined acquisition of different diagnostic modalities
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/502—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of breast, i.e. mammography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5229—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image
    • A61B6/5247—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image combining images from an ionising-radiation diagnostic technique and a non-ionising radiation diagnostic technique, e.g. X-ray and ultrasound
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Definitions

  • the invention relates to the field of imaging.
  • the invention relates to a device, a method, a computer program, a computer readable medium and a system for generating a three-dimensional model from an object of interest.
  • an X-ray mammography image of a breast is evaluated for suspicious areas that may indicate a tumor in the tissue of the breast.
  • the breast For acquiring the X-ray mammography image, the breast may be compressed and flattened between two compression paddles and an X-ray detector arrangement with a digital detector may radiograph the breast, may generate X-ray image data and the X-ray image data may be displayed on the screen of a workstation connected to the X-ray detector. A physician then may investigate and evaluate the displayed X-ray image.
  • a tomography of the breast may be acquired.
  • optical tomography which causes no exposure to possible dangerous radiation.
  • visual or infrared light is radiated onto the breast and the scattered or passed light is detected from different directions with an optical detector.
  • X-ray tomography from the raw data of the optical detector a three-dimensional representation of the object of investigation is generated.
  • the optical tomography only may provide a very diffuse image.
  • a first aspect of the invention relates to a device, for example a workstation, for generating a three-dimensional model from an object of interest.
  • the device comprises an interface for receiving optical tomography raw data acquired from the object and for receiving X-ray image data acquired from the object, a selector for selecting a reference model of the object from a plurality of reference models based on the X-ray image data and the optical tomography raw data and a generator for generating the three-dimensional model from the reference model by adjusting the reference model to the X-ray image data.
  • a first aspect of the invention relates to a method for generating a three- dimensional model from an object of interest.
  • the object of interest may by a human breast.
  • the above mentioned device may be adapted to execute the method.
  • the method comprises the steps of: receiving optical tomography raw data acquired from the object; receiving X-ray image data acquired from the object; selecting a reference model of the object from a plurality of reference models based on the X-ray image data and/or the optical tomography raw data; and generating the three-dimensional model from the reference model by adjusting the reference model to the X-ray image data.
  • the X-ray image data may be a mammography of a breast.
  • the three-dimensional model may be adjusted by parameterizing the reference model with the aid of the X-ray image data.
  • a realistic three-dimensional distribution (a three-dimensional model) of the glandular tissue of the breast may be estimated from one or more two dimensional mammograms (i.e. the X-ray image data). This estimated tissue distribution can be used as input to an optical reconstruction algorithm.
  • a further aspect of the invention relates to a system for generating a three- dimensional model, which comprises an X-ray detector arrangement adapted for acquiring X- ray image data, an optical detector arrangement adapted for acquiring optical tomography raw data; wherein the system is adapted to carry out the method as described in the above and in the following.
  • the system may be or may be part of a breast cancer screening device, which combines X-ray mammography and optical tomography in a single system.
  • the method and the device may be used in the context of breast cancer screening as part of the system, for example as reconstruction unit of a combined
  • the method and the device may be used as part of the mammography analysis chain in a Viewing/CAD workstation in order to improve CAD results.
  • the computer program may be executed on a processor of the above mentioned device or system and/or may be stored and/or loaded in a memory of the device or system.
  • a computer-readable medium may be a floppy disk, a hard disk, an USB (Universal Serial Bus) storage device, a RAM (Random Access Memory), a ROM (Read Only Memory) and an EPROM (Erasable Programmable Read Only Memory).
  • a computer readable medium may also be a data communication network, e.g. the Internet, which allows downloading a program code.
  • Fig. 1 shows a schematic view of a system according to an embodiment of the invention.
  • Fig.2 shows a diagram showing data types and a data flow according to an embodiment of the invention.
  • Fig. 3 shows a flow diagram for a method according to an embodiment of the invention.
  • Fig. 1 shows a system 10 comprising a workstation 12 and a detector arrangement 14.
  • the detector arrangement 14 comprises two compression paddles 16 which may receive and compress a human breast 18 to be examined by the system 10.
  • the object 18 may be any kind of object that may be examined with X-ray and optical tomography imaging, for example other kinds of animal and human parts.
  • the detector arrangement 14 comprises an optical detector arrangement 20 and an X-ray detector arrangement 22 that are situated around the compression paddles such that X-ray image data and optical image data may be generated from the object 18.
  • the optical detector arrangement 20 comprises a light source 24 and an optical detector 26.
  • the light source 24 may irradiate visible or infrared radiation.
  • the optical detector 26 may detect the radiation from different directions and may generate tomography raw data of the breast 18.
  • the X-ray detector arrangement 22 comprises an X-ray source 28 for generation X-rays and an X-ray detector 30 for detecting the X-rays and generating X-ray image data of the breast 18.
  • the system 10 may be a full field digital mammography system 10.
  • the workstation 12 or device 12 may control the detector arrangement 14.
  • the device 12 is adapted to control the X-ray detector arrangement 22.
  • the device 12 is adapted to control the optical detector arrangement 20.
  • the workstation 12 only receives the generated data from the detector arrangement 14.
  • the workstation 12 may comprise a display for displaying the generated image data.
  • the device 12 and the system 10 are adapted for generating a three- dimensional model from the breast 18 (the object of interest) as will be explained in detail in the following.
  • the device 12 may comprise a processor 32 that executes a computer program that performs the steps of such a method.
  • the processor 32 may comprise an interface 32 for receiving data, a selector 32 for selecting data from a database 34 and a generator 32for generating image data.
  • the device 12 comprises an interface 32 for receiving optical tomography raw data 52 acquired from the object 18 and for receiving X-ray image data 50 acquired from the object 18, a selector 32 for selecting a reference model 58 of the object 18 from a plurality of reference models based on the X-ray image data 50 and the optical tomography raw data 52 and a generator 32 for generating the three-dimensional model 60 from the reference model 58 by adjusting the reference model 58 to the X-ray image data 50.
  • Fig.2 shows a diagram showing data types and a data flow in the system 10.
  • the data types/data structures described in the following may be stored in a memory of the device 12 and may be processed by the processor 32 of the device 12.
  • the system 10 comprises an X- ray detector arrangement 22 adapted for acquiring X-ray image data 50.
  • the system 10 comprises an optical detector arrangement 20 adapted for acquiring optical tomography raw data 52.
  • the X-ray image data 50 and/or the optical tomography raw data 52 from the detector arrangement 14 may be received in the device 12 and may be used for generating a coarse model 54 of the object 18.
  • the X-ray image data 50 may represent a two-dimensional view of the object 18.
  • the X-ray image data 50 may comprise a mammography.
  • the optical tomography data 52 may represent a plurality of two-dimensional views of the object 18 and may comprise information about the three-dimensional composition of the object 18.
  • the coarse model 54 may comprise a surface model of the object 18, i.e. a model of the outer contour of the object 18.
  • an elastic deformation model 56 may be used for determining the coarse model 54 and in particular the surface model.
  • the elastic deformation model may be stored in a database 34 in the device 12.
  • the coarse model 54 may be a three-dimensional model of the object 18.
  • a model may be any type of data that comprises information of the (optional three-dimensional) structural composition of the object 18.
  • a reference model 58 may be determined from the database 34.
  • the database 34 may store a plurality of predefined reference models 58, one of which may be selected.
  • a reference model 58 may be a three-dimensional model of the object 18.
  • the device 12 comprises a database 34 for storing a plurality of reference models 58.
  • the data of the coarse model 54 is then used to adjust the reference model 58 in such a way that a three-dimensional model 60 is generated from the reference model 58 that may be a good approximation of the real composition of the object 18. This may be done by projecting the reference model 58 to a two-dimensional projection 59, comparing the two- dimensional projection with the X-ray image data 50 and adjusting the three-dimensional model 60 based on the result of the comparison.
  • the three-dimensional model 60 may be a parametric in-silico model 60 of a breast 18 and may represent realistically shaped tissue components, which may comprise skin, glandular tissue, duct system, adipose tissue and/or ligaments.
  • the three-dimensional model 60 may comprise X-ray attenuation coefficients, the coarse model 54 and/or the elastic deformation model 56.
  • the three dimensional model 60 may be used in the end, to support the generation of three-dimensional tomography data 62 from the optical tomography raw data 52.
  • the three-dimensional tomography data 62 may comprise a three-dimensional
  • the three-dimensional tomography data 62 may be used for examination of the object 18. For example, a physician may view slices through the breast 18 displayed on the device 12.
  • the three-dimensional model 60 and/or the three-dimensional tomography data 62 may be displayed by the device 12, for example by the display of the device 12.
  • a computer program stored in a memory of the workstation 12, is running on the workstation 12 which processes these data and which executes the method as described in the above and in the following.
  • Fig. 3 shows a flow diagram for a method for generating a three-dimensional model 60 from an object 18.
  • step S10 the X-ray detector arrangement 22 generates X-ray image data 50, which is received in the device 12.
  • the method comprises the step of receiving X-ray image data 50 acquired from the object 50.
  • step S12 the optical detector arrangement 20 generates optical tomography data 52, which is received in the device 12.
  • the method comprises the step of receiving optical tomography raw data 52 acquired from the object 18.
  • step S14 the device 12 generates a coarse model 54 of the object 18.
  • the coarse model 54 may comprise a surface model of the object 18.
  • a two-dimensional contour line of the object 18 may be determined, for example with a Canny edge filter or with a Gaussian mixture model. Then a distance map may be computed with respect to the detemiined breast contour. The distance map may indicate the distance of a point of the X-ray image data 50 to the contour line of the object 18.
  • the surface model which may be a three-dimensional breast contour model, may be finally generated from the two-dimensional contour line and a height value, which is computed from the normalized distance map.
  • the height value may be the distance of the paddles 16.
  • the object 18 is touching both paddles.
  • the three- dimensional surface of the object 18 may be modeled with semi-circles.
  • the system 10 and in particular the detector arrangement 14 may be arranged such that the optical tomography raw data 52 and the X-ray image data 50 are acquired without changing the position of the object 18 between the two scans, i.e. the respective detection processes of the two detector arrangements 20, 22.
  • the surface contour of the object 18 nearly does not change between the scans and it may be assumed that the surface contour of the X-ray image data 50 is equal to the surface contour of the optical tomography data 52.
  • the coarse model 54 may comprise a (coarse) density model of the object 18.
  • the percentage of fibro-glandular tissue in the object 18 may be estimated via automated object density estimation.
  • a separation of the line integral value (the attenuation value at the pixel) ⁇ ⁇ ⁇ into a contribution from adipose and glandular tissue may be computed as
  • the method comprises the step of estimating a coarse model 54 of the object 18 from the X-ray image data 50 and/or the optical tomography data 52.
  • the coarse model 54 comprises a 5 surface model of the object 18.
  • the coarse model 54 comprises a density model generated from the X-ray image data 50.
  • the density model may comprise an estimate of the local and/or the overall object density.
  • step SI 6 the device 12 determines a reference model 58.
  • the coarse model 54 in particular the surface model from step S14 and the density model from step S16 may be used to initialize a reference model 58, which may be a parametric in-silico breast model 58, comprising realistically shaped tissue components (for example skin, glandular tissue/duct system, adipose tissue, ligaments).
  • a reference model 58 which may be a parametric in-silico breast model 58, comprising realistically shaped tissue components (for example skin, glandular tissue/duct system, adipose tissue, ligaments).
  • the reference model 58 may further comprise X-ray attenuation coefficients and an elastic deformation model 56.5
  • An initial reference model may be selected from a database 34 according to the estimated overall density value ⁇ and the corresponding view position (for example LCC "left cranio-caudal", RCC “right cranio-caudal”, LMLO "left medio-lateral oblique", RMLO "right medio-lateral oblique") of the X-ray detector arrangement 22.
  • the view position may influence the compression of the object 18 and the corresponding reference model. Additional0 features such as age and total breast volume may be used for refining the selection of a
  • the database 34 of reference models 58 may be generated for example with a breast phantom generator, for example the different reference models may be modelled with an interactive modelling software.
  • the database 34 is generated from magnetic resonance imaging breast examinations.
  • the imaging data of the different examinations may be first segmented in glandular and adipose tissue and may then be categorized with respect to the before mentioned features. Then the segmented breast volumes may be mapped to a semi- ellipsoidal reference breast shape with a volume given by the reference class. Finally, all breast imaging data within one reference class may be summed and normalized to create one final reference model 58 (probability map) for each reference class.
  • the method comprises the step of selecting a reference model 58 of the object 18 from a plurality of reference models based on the coarse model 54 which is based on the X-ray image data 50 and/or the optical tomography raw data 52.
  • the plurality of reference models is stored in a database 34.
  • the reference model 58 is retrieved from the database 34 based on selection parameters comprising an estimated overall density ⁇ ; the overall object volume and/or an view direction of the X-ray image data 50.
  • the reference model 58 may be mapped to the surface model 54, thus generating a deformed reference model 58.
  • the compression force and the distance of the compression paddles 16 may also be taken into account during the modelling.
  • the reference model 58 is adjusted to the X- ray image data 50, thus becoming the three-dimensional model 60.
  • An iterative optimization process may be used during which the model parameters may be adapted in order to minimize the difference between the real mammogram and the (simulated/estimated) three-dimensional model 60.
  • the three-dimensional model 60 may be generated from the reference model 58 by adjusting parameters of the reference model 58, for example, the relationship between tissue components.
  • step S20 the device 12 projects the reference model 58 (and in further iteration steps the three dimensional model 60, i.e. the iteratively adjusted reference model 58) to a two dimensional projection 59.
  • a forward mammography projection i.e. a projection from three dimensions to two dimensions
  • the method comprises the step of projecting the (iteratively adjusted) reference model 58 to two-dimensional projection data 59.
  • step S22 the device 12 compares the two dimensional projection data 59 with the X-ray image data 50.
  • a difference measure between the X-ray image data 50 and the projection data 59, generated from the reference model 58 may be computed, for example via sum of squared differences.
  • the adjusting process may be controlled via geometry parameters (e.g. control points of surface mesh) in an iterative procedure by minimizing the sum of squared differences between the actual object data (the X-ray image data 50) and the projected simulated object data (the projection data 59) generated from the (deformed) reference model 58.
  • the method comprises the step of comparing the two-dimensional projection data 59 with the X-ray image data 50.
  • a difference measure between the two-dimensional projection data 59 and the X-ray image data 50 is calculated for comparing the two-dimensional projection data 59 and the X-ray image data 50.
  • step S24 the device 12 adjusts parameters of the (perhaps already iteratively adjusted) reference model 58.
  • the method comprises the step of adjusting the reference model 58 based on the comparison of the two-dimensional projection data 59 and the X-ray image data 50.
  • the reference model 58 is adjusted by modifying the two-dimensional projection data 59 and minimizing the difference measure.
  • the parameters (for example the relationships between tissue components, the tissue distribution) of the reference model 58 may be modified such that the difference measure is minimized.
  • inner energy terms may be applied to the reference model 58 in order to keep the basic shape of the breast and its components inside realistic ranges.
  • the (deformed) reference model 58 may be used to generate the three- dimensional model 62 by weighted back-projection of the line integral values into the
  • the method comprises the step of generating the three-dimensional model 60 from the reference model 58 by adjusting the reference model 58 to the X-ray image data 50.
  • step S26 the optical tomography raw data 52 are transformed into three- dimensional tomography data 62 with the aid of the three-dimensional model 60.
  • the three-dimensional model 60 may assure a realistic distribution of the different tissue components, the three-dimensional distribution of the fibro-glandular tissue at the optimized parameter state of the three-dimensional model 60 may be used as input estimate for the optical data reconstruction of the tomography data.
  • An iterative reconstruction of optical tomography data 52 may benefit from initialization with an estimate of the three-dimensional tissue distribution within the breast, i.e. the three-dimensional model 60.
  • the method comprises the step of generating three-dimensional tomography image data 62 from the three-dimensional model 60 and the optical tomography image raw data 52.
  • the method may also be a method of reconstruction three- dimensional tomography image data 62.
  • the object 18 may be repositioned between the acquisition of the mammogram and the optical tomography data, i.e. between steps S10 and S12.
  • the reference model 58, and in particular the estimated three- dimensional distribution of the fibro-glandular tissue may need to be deformed in order to match the positioning of the object 18 during the optical data acquisition in step S12.
  • the surface model 54 may be reconstructed in both positioning states (for example by using estimation techniques purely based on the X-ray data 50 / optical data 52 which is available and/or by additional use of fiducial markers, structured light, time-of-flight range scanners, or equivalent methods).
  • a first surface model of the object 18 is estimated from the X-ray image data 50 and a second surface model of the object 18 is estimated from the optical tomography data 52.
  • an elastic deformation model 56 is used to estimate the deformation of the inner breast tissue (namely of the fibro-glandular tissue) based on the known two surface shapes.
  • the first surface model is mapped to the second surface model with an elastic deformation model of the object 18.
  • the deformed reference model 58 may be used to enhance the optical tomography reconstruction process as described in the above.

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Abstract

Afin de générer un modèle tridimensionnel (60) d'un objet d'intérêt, des données brutes de tomographie optique acquises à partir dudit objet et des données d'imagerie par rayons X acquises à partir dudit objet (50) sont utilisées pour sélectionner un modèle de référence de l'objet (18) parmi une pluralité de modèles de référence fondés sur les données d'imagerie par rayons X et sur les données brutes de tomographie optique. Le modèle tridimensionnel est généré à partir dudit modèle de référence en ajustant ce dernier aux données d'imagerie par rayons X.
PCT/IB2012/054368 2011-09-13 2012-08-27 Génération d'un modèle tridimensionnel d'un objet d'intérêt WO2013038284A1 (fr)

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US201161533857P 2011-09-13 2011-09-13
US61/533,857 2011-09-13

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3628214A1 (fr) * 2018-09-28 2020-04-01 Siemens Healthcare GmbH Reconstruction d'une image de faible énergie à partir d'une image scanographique
US11213247B2 (en) 2016-06-30 2022-01-04 Koninklijke Philips N.V. Generation and personalization of a statistical breast model

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007111669A2 (fr) * 2005-12-22 2007-10-04 Visen Medical, Inc. Systeme d'imagerie tomographique a rayons x et optique combine
WO2009060351A1 (fr) * 2007-11-09 2009-05-14 Koninklijke Philips Electronics N.V. Appareil et procédé pour générer une carte d'atténuation
WO2012071682A1 (fr) * 2010-11-30 2012-06-07 中国科学院自动化研究所 Système et procédé de tomographie optique tridimensionnelle multimode basés sur la spécificité

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007111669A2 (fr) * 2005-12-22 2007-10-04 Visen Medical, Inc. Systeme d'imagerie tomographique a rayons x et optique combine
WO2009060351A1 (fr) * 2007-11-09 2009-05-14 Koninklijke Philips Electronics N.V. Appareil et procédé pour générer une carte d'atténuation
WO2012071682A1 (fr) * 2010-11-30 2012-06-07 中国科学院自动化研究所 Système et procédé de tomographie optique tridimensionnelle multimode basés sur la spécificité

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11213247B2 (en) 2016-06-30 2022-01-04 Koninklijke Philips N.V. Generation and personalization of a statistical breast model
EP3628214A1 (fr) * 2018-09-28 2020-04-01 Siemens Healthcare GmbH Reconstruction d'une image de faible énergie à partir d'une image scanographique

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