[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Anaya-Isaza et al., 2022 - Google Patents

Detection of diabetes mellitus with deep learning and data augmentation techniques on foot thermography

Anaya-Isaza et al., 2022

View PDF
Document ID
17809408954107810444
Author
Anaya-Isaza A
Zequera-Diaz M
Publication year
Publication venue
IEEE Access

External Links

Snippet

Diabetes mellitus (DM) is a metabolic disorder characterized by increased blood glucose. The pathology can manifest itself with different conditions, including neuropathy, the main consequence of diabetic disease. Statistics show worrying figures worldwide, diagnosed an …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • 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
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • 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
    • 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
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • 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
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • 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
    • G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • 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
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models

Similar Documents

Publication Publication Date Title
Rehman et al. Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture
Al-Yasriy et al. Diagnosis of lung cancer based on CT scans using CNN
Islam et al. Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images
Goyal et al. Dfunet: Convolutional neural networks for diabetic foot ulcer classification
Filali et al. Efficient fusion of handcrafted and pre-trained CNNs features to classify melanoma skin cancer
Anaya-Isaza et al. Detection of diabetes mellitus with deep learning and data augmentation techniques on foot thermography
Shrivastava et al. First review on psoriasis severity risk stratification: An engineering perspective
Aijaz et al. Deep learning application for effective classification of different types of psoriasis
Barbosa et al. Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images
Hsueh et al. Human behavior recognition from multiview videos
Petrellis A review of image processing techniques common in human and plant disease diagnosis
Magdy et al. Performance Enhancement of Skin Cancer Classification Using Computer Vision
Bozkurt Skin lesion classification on dermatoscopic images using effective data augmentation and pre-trained deep learning approach
Molaei et al. FDCNet: Presentation of the fuzzy CNN and fractal feature extraction for detection and classification of tumors
CN115131642A (en) Multi-modal medical data fusion system based on multi-view subspace clustering
Natarajan et al. Efficient segmentation of brain tumor using FL-SNM with a metaheuristic approach to optimization
Alshayeji et al. Early detection of diabetic foot ulcers from thermal images using the bag of features technique
Hussain et al. Machine learning-based lungs cancer detection using reconstruction independent component analysis and sparse filter features
Lanjewar et al. CNN and transfer learning methods with augmentation for citrus leaf diseases detection using PaaS cloud on mobile
Vipin et al. Detection of melanoma using deep learning techniques: A review
Venkatesan et al. NFU-Net: an automated framework for the detection of neurotrophic foot ulcer using deep convolutional neural network
Jain et al. A convolutional neural network with meta-feature learning for wireless capsule endoscopy image classification
Zhang et al. Multi-feature representation for burn depth classification via burn images
Yousef et al. Classification of Diabetic Foot Thermal Images Using Deep Convolutional Neural Network.
Goyal et al. Musculoskeletal abnormality detection in medical imaging using GnCNNr (group normalized convolutional neural networks with regularization)