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

Quan et al., 2021 - Google Patents

XPGAN: X-ray projected generative adversarial network for improving Covid-19 image Classification

Quan et al., 2021

View PDF
Document ID
237366760696719308
Author
Quan T
Thanh H
Huy T
Chanh N
Anh N
Vu P
Nam N
Tuong T
Dien V
Van Giang B
Trung B
Truong S
Publication year
Publication venue
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)

External Links

Snippet

This work aims to fight against the current outbreak pandemic by developing a method to classify suspected infected COVID-19 cases. Driven by the urgency, due to the vastly increased number of patients and deaths worldwide, we rely on situationally pragmatic chest …
Continue reading at scholar.archive.org (PDF) (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
    • 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
    • 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
    • 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
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2211/00Image generation
    • G06T2211/40Computed tomography
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/003Reconstruction from projections, e.g. tomography
    • G06T11/005Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
    • 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
    • G06T3/0031Geometric 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
    • G06T3/0037Reshaping or unfolding a 3D tree structure onto a 2D plane

Similar Documents

Publication Publication Date Title
Laradji et al. A weakly supervised consistency-based learning method for covid-19 segmentation in ct images
Shiri et al. Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network
Corbella et al. Applications of deep learning in dentistry
Nomura et al. Projection‐domain scatter correction for cone beam computed tomography using a residual convolutional neural network
Quan et al. XPGAN: X-ray projected generative adversarial network for improving Covid-19 image Classification
Liu et al. Deep learning-based evaluation of the relationship between mandibular third molar and mandibular canal on CBCT
Padma et al. Deep learning based chest x-ray image as a diagnostic tool for covid-19
JP4392344B2 (en) Tomographic reconstruction of small objects using a priori knowledge
Caliskan et al. A pilot study of a deep learning approach to submerged primary tooth classification and detection
Kohlakala et al. Deep learning-based dental implant recognition using synthetic X-ray images
EP4002387A1 (en) Cad device and method for analysing medical images
Mostafapour et al. A Novel Unsupervised Approach for COVID-19 Lung Lesion Detection Based on Object Completion Technique
Sotoudeh-Paima et al. Photon-counting CT versus conventional CT for COPD quantifications: intra-scanner optimization and inter-scanner assessments using virtual imaging trials
Makarovskikh et al. Automatic classification Infectious disease X-ray images based on Deep learning Algorithms
Nagaoka et al. A deep learning system to diagnose COVID-19 pneumonia using masked lung CT images to avoid AI-generated COVID-19 diagnoses that include data outside the lungs
Astuti et al. The Sensitivity and Specificity of YOLO V4 for Tooth Detection on Panoramic Radiographs
Mangalagiri et al. Toward generating synthetic CT volumes using a 3D-conditional generative adversarial network
Liu et al. [Retracted] Application of 64‐Slice Spiral CT Imaging Technology Based on Smart Medical Augmented Reality in the Diagnosis of Foreign Bodies in the Respiratory Tract in Children
Mozaffary et al. Integration of fully automated computer-aided pulmonary nodule detection into CT pulmonary angiography studies in the emergency department: effect on workflow and diagnostic accuracy
Tan et al. Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest x-ray for covid-19
Norman et al. The applicability of Dual-Energy Computed Tomography (DECT) in forensic odontology–A review
Rodríguez Pérez et al. Methodology to create 3D models of COVID-19 pathologies for virtual clinical trials
Ünsal et al. Automatic detection of dentigerous cysts on panoramic radiographs: a deep learning study
Kolarkodi et al. Artificial intelligence in diagnosis of oral diseases: A systematic review
Venkatesan et al. Computed tomography scan simulation techniques: a survey