Gudur et al., 2014 - Google Patents
A unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planningGudur et al., 2014
View PDF- Document ID
- 9907002903055071127
- Author
- Gudur M
- Hara W
- Le Q
- Wang L
- Xing L
- Li R
- Publication year
- Publication venue
- Physics in Medicine & Biology
External Links
Snippet
MRI significantly improves the accuracy and reliability of target delineation in radiation therapy for certain tumors due to its superior soft tissue contrast compared to CT. A treatment planning process with MRI as the sole imaging modality will eliminate systematic CT/MRI co …
- 238000001959 radiotherapy 0 title abstract description 16
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
-
- 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
- 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
- G06T2207/10104—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
- G06T2207/10116—X-ray image
-
- 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
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Gudur et al. | A unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planning | |
| Liu et al. | Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning | |
| Arabi et al. | Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET–MRI-guided radiotherapy treatment planning | |
| Lei et al. | MRI-based synthetic CT generation using semantic random forest with iterative refinement | |
| Dong et al. | Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging | |
| Lei et al. | MRI‐only based synthetic CT generation using dense cycle consistent generative adversarial networks | |
| Fu et al. | Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging | |
| Hsu et al. | Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiation therapy | |
| Sjölund et al. | Generating patient specific pseudo-CT of the head from MR using atlas-based regression | |
| Bezrukov et al. | MR-based PET attenuation correction for PET/MR imaging | |
| Ladefoged et al. | Region specific optimization of continuous linear attenuation coefficients based on UTE (RESOLUTE): application to PET/MR brain imaging | |
| Schulz et al. | Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data | |
| Pace et al. | Comparison of whole-body PET/CT and PET/MRI in breast cancer patients: lesion detection and quantitation of 18F-deoxyglucose uptake in lesions and in normal organ tissues | |
| Edmund et al. | A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times | |
| Burgos et al. | Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning | |
| Arabi et al. | Truncation compensation and metallic dental implant artefact reduction in PET/MRI attenuation correction using deep learning-based object completion | |
| Khalifé et al. | Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately? | |
| Hsu et al. | Quantitative characterizations of ultrashort echo (UTE) images for supporting air–bone separation in the head | |
| Leibfarth et al. | Automatic delineation of tumor volumes by co-segmentation of combined PET/MR data | |
| Yip et al. | Development and evaluation of an articulated registration algorithm for human skeleton registration | |
| Park et al. | Simultaneous tumor and surrogate motion tracking with dynamic MRI for radiation therapy planning | |
| Maspero et al. | Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy | |
| De Silva et al. | Registration of MRI to intraoperative radiographs for target localization in spinal interventions | |
| Touati et al. | A feature invariant generative adversarial network for head and neck MRI/CT image synthesis | |
| Eldib et al. | Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging |