Liu et al., 2021 - Google Patents
Automated radiographic evaluation of adenoid hypertrophy based on VGG-LiteLiu et al., 2021
View PDF- Document ID
- 13229087037602346405
- Author
- Liu J
- Li S
- Cai Y
- Lan D
- Lu Y
- Liao W
- Ying S
- Zhao Z
- Publication year
- Publication venue
- Journal of Dental Research
External Links
Snippet
Adenoid hypertrophy is a pathological hyperplasia of the adenoids, which may cause snoring and apnea, as well as impede breathing during sleep. The lateral cephalogram is commonly used by dentists to screen for adenoid hypertrophy, but it is tedious and time …
- 201000003462 adenoid hypertrophy 0 title abstract description 61
Classifications
-
- 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
- G06F19/34—Computer-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
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- 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
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- 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
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/328—Health insurance management, e.g. payments or protection against fraud
-
- 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
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/321—Management of medical image data, e.g. communication or archiving systems such as picture archiving and communication systems [PACS] or related medical protocols such as digital imaging and communications in medicine protocol [DICOM]; Editing of medical image data, e.g. adding diagnosis information
-
- 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
- G06F19/34—Computer-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
- G06F19/3487—Medical report generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
- G06Q50/24—Patient record management
-
- 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
-
- 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
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
-
- 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
- A61B5/01—Measuring temperature of body parts; Diagnostic temperature sensing, e.g. for malignant or inflammed tissue
- A61B5/015—By temperature mapping of body part
-
- 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
-
- 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
- A61B5/48—Other medical applications
-
- 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
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
-
- 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
- A61B5/0059—Detecting, measuring or recording for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0062—Arrangements for scanning
-
- 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
- A61B5/117—Identification of persons
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | Automated radiographic evaluation of adenoid hypertrophy based on VGG-Lite | |
Yu et al. | Automated skeletal classification with lateral cephalometry based on artificial intelligence | |
Esteva et al. | Deep learning-enabled medical computer vision | |
Lee et al. | Automated detection of TMJ osteoarthritis based on artificial intelligence | |
Hwang et al. | Development and validation of a deep learning–based automated detection algorithm for major thoracic diseases on chest radiographs | |
Wei et al. | Evaluation of a deep neural network for automated classification of colorectal polyps on histopathologic slides | |
Ilhan et al. | Improving oral cancer outcomes with imaging and artificial intelligence | |
Casalegno et al. | Caries detection with near-infrared transillumination using deep learning | |
Soda et al. | AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study | |
Ahn et al. | Association of artificial intelligence–aided chest radiograph interpretation with reader performance and efficiency | |
Menzies et al. | The performance of SolarScan: an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma | |
Rania et al. | Semantic segmentation of diabetic foot ulcer images: dealing with small dataset in DL approaches | |
Day et al. | Evaluation of a weightbearing CT artificial intelligence-based automatic measurement for the M1-M2 intermetatarsal angle in hallux valgus | |
Qiu et al. | Pre-training in medical data: A survey | |
Pai et al. | Artificial intelligence–aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs | |
Ghabri et al. | Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers | |
Dinesh et al. | Machine learning in the detection of oral lesions with clinical intraoral images | |
Zhang et al. | Comparison of chest radiograph captions based on natural language processing vs completed by radiologists | |
Wang et al. | A Multiscale Attentional Unet Model for Automatic Segmentation in Medical Ultrasound Images | |
Krones et al. | Review of multimodal machine learning approaches in healthcare | |
Azhari et al. | Artificial intelligence (AI) in restorative dentistry: Performance of AI models designed for detection of interproximal carious lesions on primary and permanent dentition | |
Rubegni et al. | The role of dermoscopy and digital dermoscopy analysis in the diagnosis of pigmented skin lesions | |
Choi et al. | Mask R-CNN based multiclass segmentation model for endotracheal intubation using video laryngoscope | |
Ünsal et al. | Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers | |
Chen et al. | Automatic and visualized grading of dental caries using deep learning on panoramic radiographs |