[go: up one dir, main page]

Chen et al., 2010 - Google Patents

Segmentation of lymph node regions in head-and-neck CT images using a combination of registration and active shape model

Chen et al., 2010

View PDF
Document ID
3394971110665138059
Author
Chen A
Deeley M
Niermann K
Moretti L
Dawant B
Publication year
Publication venue
Medical Imaging 2010: Image Processing

External Links

Snippet

Segmenting the lymph node regions in head and neck CT images has been a challenging topic in the area of medical image segmentation. The method proposed herein implements an atlas-based technique constrained by an active shape model (ASM) to segment the level …
Continue reading at drive.google.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30048—Heart; Cardiac
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10104—Positron emission tomography [PET]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10084—Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G06T2207/20156—Automatic seed setting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0068—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for image registration, e.g. elastic snapping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves involving electronic or nuclear magnetic resonance, e.g. magnetic resonance imaging

Similar Documents

Publication Publication Date Title
US11455732B2 (en) Knowledge-based automatic image segmentation
Foskey et al. Large deformation three-dimensional image registration in image-guided radiation therapy
US8787648B2 (en) CT surrogate by auto-segmentation of magnetic resonance images
US7817836B2 (en) Methods for volumetric contouring with expert guidance
EP1636753B1 (en) 3d image segmentation
US10149987B2 (en) Method and system for generating synthetic electron density information for dose calculations based on MRI
US9082169B2 (en) Longitudinal monitoring of pathology
Ibragimov et al. Segmentation of pathological structures by landmark-assisted deformable models
Lu et al. Simultaneous nonrigid registration, segmentation, and tumor detection in MRI guided cervical cancer radiation therapy
US9727975B2 (en) Knowledge-based automatic image segmentation
Liu et al. Accuracy validation for medical image registration algorithms: a review
Chen et al. Combining registration and active shape models for the automatic segmentation of the lymph node regions in head and neck CT images
Martin et al. A multiphase validation of atlas-based automatic and semiautomatic segmentation strategies for prostate MRI
Zhao et al. Research on 3D reconstruction algorithm of medical CT image based on parallel contour
US20080285822A1 (en) Automated Stool Removal Method For Medical Imaging
Skalski et al. Using ASM in CT data segmentaion for prostate radiotherapy
Faber et al. Automatic alignment of myocardial perfusion images with contrast-enhanced cardiac computed tomography
Whitmarsh et al. 3D bone mineral density distribution and shape reconstruction of the proximal femur from a single simulated DXA image: an in vitro study
Chen et al. Segmentation of lymph node regions in head-and-neck CT images using a combination of registration and active shape model
Teng et al. Head and neck lymph node region delineation using a hybrid image registration method
Wodzinski et al. Application of B-splines FFD image registration in breast cancer radiotherapy planning
Kos et al. Comparison of ASM and AAM-based segmentation of prostate image in the CT scans for radiotherapy planning
Zhang Liver vessel segmentation and accurate landmark pairs detection for quantitative liver deformable image registration verification
Díaz-Parra et al. Fully automatic spinal canal segmentation for radiation therapy using a gradient vector flow-based method on computed tomography images: A preliminary study
Chowdhury et al. Linked Statistical Shape Models for multi-modal segmentation of the prostate on MRI-CT for radiotherapy planning