Cairone et al., 2022 - Google Patents
Robustness of radiomics features to varying segmentation algorithms in magnetic resonance imagesCairone et al., 2022
- Document ID
- 4162904671245218682
- Author
- Cairone L
- Benfante V
- Bignardi S
- Marinozzi F
- Yezzi A
- Tuttolomondo A
- Salvaggio G
- Bini F
- Comelli A
- Publication year
- Publication venue
- International Conference on Image Analysis and Processing
External Links
Snippet
Aim: To verify the accuracy of different segmentation algorithms applied on a dataset of 50 patients suffering from enlargement of the median lobe of the prostate district, to establish whether it is possible to support the work of medical physicians in radiomics analyses …
- 230000011218 segmentation 0 title abstract description 58
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
- G06T2207/10088—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
- G06T7/0014—Biomedical image inspection using an image reference approach
-
- 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
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
-
- 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
- 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
- G06K9/6267—Classification techniques
-
- 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
- G06T3/0031—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for topological mapping of a higher dimensional structure on a lower dimensional surface
- G06T3/0037—Reshaping or unfolding a 3D tree structure onto a 2D plane
-
- 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
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11967072B2 (en) | Three-dimensional object segmentation of medical images localized with object detection | |
| Sun et al. | Multiparametric MRI and radiomics in prostate cancer: a review | |
| Liu et al. | Advances in deep learning-based medical image analysis | |
| Wang et al. | A deep learning‐based autosegmentation of rectal tumors in MR images | |
| Acharya et al. | Towards precision medicine: from quantitative imaging to radiomics | |
| Lu et al. | A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning | |
| Gao et al. | Prostate segmentation by sparse representation based classification | |
| Cairone et al. | Robustness of radiomics features to varying segmentation algorithms in magnetic resonance images | |
| Guo et al. | A novel method to model hepatic vascular network using vessel segmentation, thinning, and completion | |
| Zeng et al. | Prostate segmentation in transrectal ultrasound using magnetic resonance imaging priors | |
| Ayyad et al. | A new framework for precise identification of prostatic adenocarcinoma | |
| Gates et al. | Glioma segmentation and a simple accurate model for overall survival prediction | |
| Fashandi et al. | An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U‐nets | |
| Dillman et al. | Current and emerging artificial intelligence applications for pediatric abdominal imaging | |
| Jaffar et al. | Ensemble classification of pulmonary nodules using gradient intensity feature descriptor and differential evolution | |
| Sekaran et al. | 3D brain slice classification and feature extraction using Deformable Hierarchical Heuristic Model | |
| Benfante et al. | Grading and Staging of Bladder Tumors Using Radiomics Analysis in Magnetic Resonance Imaging | |
| Xu et al. | Simultaneous segmentation of multiple regions in 3D bladder MRI by efficient convex optimization of coupled surfaces | |
| Bibars et al. | Cross-modality deep transfer learning: Application to liver segmentation in ct and mri | |
| Wu et al. | Automatic segmentation of ultrasound tomography image | |
| Giv et al. | Lung segmentation using active shape model to detect the disease from chest radiography | |
| Li et al. | Clinical study of diffusion-weighted imaging in the diagnosis of liver focal lesion | |
| Sharma et al. | Importance of deep learning models to perform segmentation on medical imaging modalities | |
| Tanabe et al. | Development of a quantitative method based on the hill-shading technique for assessing morphological changes in the bone during image-guided radiotherapy for bone metastasis | |
| Tabrizi et al. | Acetabular cartilage segmentation in CT arthrography based on a bone-normalized probabilistic atlas |