Leavens et al., 2008 - Google Patents
Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck regionLeavens et al., 2008
View PDF- Document ID
- 357645303615157849
- Author
- Leavens C
- Vik T
- Schulz H
- Allaire S
- Kim J
- Dawson L
- O'Sullivan B
- Breen S
- Jaffray D
- Pekar V
- Publication year
- Publication venue
- Medical Imaging 2008: Image Processing
External Links
Snippet
Manual contouring of target volumes and organs at risk in radiation therapy is extremely time- consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves …
- 230000011218 segmentation 0 title abstract description 21
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
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- 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
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- 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
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K2209/05—Recognition of patterns in medical or anatomical images
- G06K2209/051—Recognition of patterns in medical or anatomical images of internal organs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ghose et al. | A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images | |
US7693564B2 (en) | System, apparatus and method for forensic facial approximation | |
US8437521B2 (en) | Systems and methods for automatic vertebra edge detection, segmentation and identification in 3D imaging | |
CN106485695B (en) | Medical image Graph Cut dividing method based on statistical shape model | |
Ma et al. | Hierarchical segmentation and identification of thoracic vertebra using learning-based edge detection and coarse-to-fine deformable model | |
EP1899917B1 (en) | Method and apparatus for atlas-assisted interpretation of magnetic resonance diffusion and prefusion images | |
US8861891B2 (en) | Hierarchical atlas-based segmentation | |
Gao et al. | A coupled global registration and segmentation framework with application to magnetic resonance prostate imagery | |
He et al. | Fast automatic 3D liver segmentation based on a three‐level AdaBoost‐guided active shape model | |
Gu et al. | Bidirectional elastic image registration using B-spline affine transformation | |
Yu et al. | Unsupervised 3D PET-CT image registration method using a metabolic constraint function and a multi-domain similarity measure | |
Matsopoulos et al. | Thoracic non-rigid registration combining self-organizing maps and radial basis functions | |
Chen et al. | Combining registration and active shape models for the automatic segmentation of the lymph node regions in head and neck CT images | |
Merck et al. | Training models of anatomic shape variability | |
Leavens et al. | Validation of automatic landmark identification for atlas-based segmentation for radiation treatment planning of the head-and-neck region | |
CN109671131B (en) | Image correction method, device, medical image equipment and storage medium | |
Szmul et al. | Supervoxels for graph cuts-based deformable image registration using guided image filtering | |
Skalski et al. | Using ASM in CT data segmentaion for prostate radiotherapy | |
Zhao et al. | Robust shape-constrained active contour for whole heart segmentation in 3-D CT images for radiotherapy planning | |
Wodzinski et al. | Application of demons image registration algorithms in resected breast cancer lodge localization | |
Lu et al. | A coupled segmentation and registration framework for medical image analysis using robust point matching and active shape model | |
Wodzinski et al. | Usage of ICP algorithm for initial alignment in B-splines FFD image registration in breast cancer radiotherapy planning | |
Trabelsi et al. | 3D Active Shape Model for CT-scan liver segmentation | |
Osechinskiy et al. | Deformable registration of histological sections to brain MR images using a hybrid boundary-based slice-to-volume approach | |
Fookes et al. | Rigid and non-rigid image registration and its association with mutual information: A review |