Schoenahl et al., 2004 - Google Patents
Towards optimal model-based partial volume effect correction in oncological PET imagingSchoenahl et al., 2004
View PDF- Document ID
- 9765823280313825787
- Author
- Schoenahl F
- Zaidi H
- Publication year
- Publication venue
- IEEE Symposium Conference Record Nuclear Science 2004.
External Links
Snippet
Quantification of tumor uptake in nuclear medicine requires the assessment of the tumor size. We propose a method based on simple ellipsoidal models which only require the reconstructed image data and scanner physical parameters. The method uses simple image …
- 230000000694 effects 0 title abstract description 17
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
- G06T2207/10—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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- 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
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/006—Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/005—Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
-
- 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
- G06T2207/10116—X-ray 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
- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/424—Iterative
-
- 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
- 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
-
- 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
- G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gong et al. | Iterative PET image reconstruction using convolutional neural network representation | |
Thomas et al. | PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography | |
US8058601B2 (en) | Determining a multimodal pixon map for tomographic-image reconstruction | |
Geets et al. | A gradient-based method for segmenting FDG-PET images: methodology and validation | |
US9349198B2 (en) | Robust artifact reduction in image reconstruction | |
Mehranian et al. | PET image reconstruction using multi-parametric anato-functional priors | |
CN106920246B (en) | Uncertainty map for segmentation in the presence of metal artifacts | |
Fung et al. | Cerebral blood flow with [15O] water PET studies using an image-derived input function and MR-defined carotid centerlines | |
Naqa et al. | Deblurring of breathing motion artifacts in thoracic PET images by deconvolution methods | |
EP2992504B1 (en) | De-noised reconstructed image data edge improvement | |
Le Pogam et al. | Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography | |
CN108292428A (en) | The system and method for image reconstruction | |
Beekman et al. | Selection of task-dependent diffusion filters for the post-processing of SPECT images | |
Tang et al. | Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy | |
Barbee et al. | A method for partial volume correction of PET-imaged tumor heterogeneity using expectation maximization with a spatially varying point spread function | |
US8160340B2 (en) | Reconstructing a tomographic image | |
Eldib et al. | Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging | |
Chun et al. | Post-reconstruction non-local means filtering methods using CT side information for quantitative SPECT | |
US8086011B2 (en) | Reconstructing a tomographic image | |
Nuyts et al. | Evaluation of maximum-likelihood based attenuation correction in positron emission tomography | |
Zhu et al. | Deconvolution-based partial volume correction of PET images with parallel level set regularization | |
Kim et al. | An effective post-filtering framework for 3-D PET image denoising based on noise and sensitivity characteristics | |
Dikaios et al. | Improved motion‐compensated image reconstruction for PET using sensitivity correction per respiratory gate and an approximate tube‐of‐response backprojector | |
Gao et al. | Voxel-based partial volume correction of PET images via subtle MRI guided non-local means regularization | |
Shieh et al. | Improving thoracic four-dimensional cone-beam CT reconstruction with anatomical-adaptive image regularization (AAIR) |