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

Aguirre Nilsson et al., 2018 - Google Patents

Classification of ulcer images using convolutional neural networks

Aguirre Nilsson et al., 2018

View PDF
Document ID
6435234251193172482
Author
Aguirre Nilsson C
Velic M
Publication year

External Links

Snippet

The use of artificial intelligence has increased within a variety of different fields the last decade, including the area of health care. Machine learning algorithms have already been successfully used in eg skin cancer detection in images, indicating its potential for being …
Continue reading at odr.chalmers.se (PDF) (other versions)

Classifications

    • 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
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • 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
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • G06K9/4604Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • 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
    • 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
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • 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
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color 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
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Biswas et al. State-of-the-art review on deep learning in medical imaging
Liu et al. Fine-tuning pre-trained convolutional neural networks for gastric precancerous disease classification on magnification narrow-band imaging images
Zhang et al. Automatic skin lesion segmentation by coupling deep fully convolutional networks and shallow network with textons
Zhang et al. A deep learning outline aimed at prompt skin cancer detection utilizing gated recurrent unit networks and improved orca predation algorithm
Hu et al. AS-Net: Attention Synergy Network for skin lesion segmentation
Kotia et al. Few shot learning for medical imaging
Santosh et al. Deep learning models for medical imaging
Niyaz et al. Advances in deep learning techniques for medical image analysis
Khan et al. Knowledge distillation approach towards melanoma detection
Aguirre Nilsson et al. Classification of ulcer images using convolutional neural networks
Hampiholi Medical Imaging Enhancement with Ai Models for Automatic Disease Detection and Classification Based on Medical Images
Riaz et al. A comprehensive joint learning system to detect skin cancer
Huang et al. Breast cancer diagnosis based on hybrid SqueezeNet and improved chef-based optimizer
Üzen Convmixer-based encoder and classification-based decoder architecture for breast lesion segmentation in ultrasound images
Sankari et al. Automated detection of retinopathy of prematurity using quantum machine learning and deep learning techniques
Sharma et al. Solving image processing critical problems using machine learning
Hadi et al. Comparison Between Convolutional Neural Network CNN and SVM in Skin Cancer Images Recognition
Selvia et al. Skin lesion detection using feature extraction approach
Baskaran et al. MSRFNet for skin lesion segmentation and deep learning with hybrid optimization for skin cancer detection
Akella et al. An advanced deep learning method to detect and classify diabetic retinopathy based on color fundus images
Xin et al. Transformer guided self-adaptive network for multi-scale skin lesion image segmentation
Khani Medical image segmentation using machine learning
Farea et al. A hybrid deep learning skin cancer prediction framework
Niranjana et al. Enhanced Skin Diseases Prediction using DenseNet-121: Leveraging Dataset Diversity for High Accuracy Classification
Anisuzzaman Novel Deep Neural Network for Medical Image Classification