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

Korez et al., 2020 - Google Patents

A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation

Korez et al., 2020

Document ID
2647072894356202703
Author
Korez R
Putzier M
Vrtovec T
Publication year
Publication venue
European Spine Journal

External Links

Snippet

Purpose The purpose of this study is to evaluate the performance of a novel deep learning (DL) tool for fully automated measurements of the sagittal spinopelvic balance from X-ray images of the spine in comparison with manual measurements. Methods Ninety-seven …
Continue reading at link.springer.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
    • G06T2207/30008Bone
    • 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
    • G06T2207/10116X-ray image
    • 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
    • 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
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0068Geometric 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
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/45For evaluating or diagnosing the musculoskeletal system or teeth
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation

Similar Documents

Publication Publication Date Title
Korez et al. A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation
US11707327B2 (en) Systems and methods for modeling spines and treating spines based on spine models
Galbusera et al. Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach
US10874460B2 (en) Systems and methods for modeling spines and treating spines based on spine models
US11207135B2 (en) Systems and methods for modeling spines and treating spines based on spine models
Sarkalkan et al. Statistical shape and appearance models of bones
US8126249B2 (en) Methods of and system for detection and tracking of osteoporosis
JP5337845B2 (en) How to perform measurements on digital images
US20210174503A1 (en) Method, system and storage medium with a program for the automatic analysis of medical image data
US8676298B2 (en) Medical image alignment apparatus, method, and program
Aubin et al. Reliability and accuracy analysis of a new semiautomatic radiographic measurement software in adult scoliosis
US20240046090A1 (en) Spinal surgery outcome prediction
US11883219B2 (en) Artificial intelligence intra-operative surgical guidance system and method of use
Jouffroy et al. Improved acetabular fracture diagnosis after training in a CT-based method
Suri et al. Vertebral deformity measurements at MRI, CT, and radiography using deep learning
US9576353B2 (en) Method for verifying the relative position of bone structures
Meynen et al. Advanced quantitative 3D imaging improves the reliability of the classification of acetabular defects
Lee et al. Computer-aided diagnosis for determining sagittal spinal curvatures using deep learning and radiography
Rosenthal et al. 3D-MRI versus 3D-CT in the evaluation of glenoid deformity in glenohumeral arthritis using Dixon 3D FLASH sequence
US11610305B2 (en) Method and system for postural analysis and measuring anatomical dimensions from a radiographic image using machine learning
Anitha et al. Identification of apical vertebra for grading of idiopathic scoliosis using image processing
Makhdoomi et al. Development of Scoliotic Spine Severity Detection using Deep Learning Algorithms
Haselhuhn et al. Spine surgeon versus AI algorithm full-length radiographic measurements: a validation study of complex adult spinal deformity patients
Yuh et al. Deep learning-assisted quantitative measurement of thoracolumbar fracture features on lateral radiographs
US20230169644A1 (en) Computer vision system and method for assessing orthopedic spine condition