Nothing Special   »   [go: up one dir, main page]

Su et al., 2023 - Google Patents

Res-DUnet: A small-region attentioned model for cardiac MRI-based right ventricular segmentation

Su et al., 2023

Document ID
14575305407840985751
Author
Su C
Ma J
Zhou Y
Li P
Tang Z
Publication year
Publication venue
Applied Soft Computing

External Links

Snippet

Right ventricular function has been associated with a variety of cardiovascular diseases. In the clinical study of right ventricular function, an important step is segmentation of the right ventricle so that functional indicators of the heart can be quantified and evaluated based on …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30048Heart; Cardiac
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • G06T7/0014Biomedical image inspection using an image reference approach
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10088Magnetic resonance imaging [MRI]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10104Positron emission tomography [PET]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20092Interactive image processing based on input by user
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Zhuang et al. Evaluation of algorithms for multi-modality whole heart segmentation: an open-access grand challenge
US9968257B1 (en) Volumetric quantification of cardiovascular structures from medical imaging
US11182896B2 (en) Automated segmentation of organ chambers using deep learning methods from medical imaging
US11024025B2 (en) Automatic quantification of cardiac MRI for hypertrophic cardiomyopathy
Leiner et al. Machine learning in cardiovascular magnetic resonance: basic concepts and applications
Noothout et al. Deep learning-based regression and classification for automatic landmark localization in medical images
Dangi et al. A distance map regularized CNN for cardiac cine MR image segmentation
Wolterink et al. Automatic segmentation and disease classification using cardiac cine MR images
Sander et al. Automatic segmentation with detection of local segmentation failures in cardiac MRI
EP3803687A1 (en) Methods and systems for utilizing quantitative imaging
Liu et al. Automated cardiac segmentation of cross-modal medical images using unsupervised multi-domain adaptation and spatial neural attention structure
US10878564B2 (en) Systems and methods for processing 3D anatomical volumes based on localization of 2D slices thereof
Dong et al. DeU-Net 2.0: Enhanced deformable U-Net for 3D cardiac cine MRI segmentation
Xu et al. BMAnet: Boundary mining with adversarial learning for semi-supervised 2D myocardial infarction segmentation
Tilborghs et al. Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
Ammari et al. A review of approaches investigated for right ventricular segmentation using short‐axis cardiac MRI
Suinesiaputra et al. Deep learning analysis of cardiac MRI in legacy datasets: multi-ethnic study of atherosclerosis
Sfakianakis et al. GUDU: Geometrically-constrained Ultrasound Data augmentation in U-Net for echocardiography semantic segmentation
Su et al. Res-DUnet: A small-region attentioned model for cardiac MRI-based right ventricular segmentation
Zuluaga et al. Voxelwise atlas rating for computer assisted diagnosis: Application to congenital heart diseases of the great arteries
Peña-Solórzano et al. Findings from machine learning in clinical medical imaging applications–Lessons for translation to the forensic setting
Ribeiro et al. Left ventricle segmentation in cardiac MR: A systematic mapping of the past decade
Sander et al. Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations
Pal et al. A fully connected reproducible SE-UResNet for multiorgan chest radiographs segmentation
Graves et al. Siamese pyramidal deep learning network for strain estimation in 3D cardiac cine-MR