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

Poranki et al., 2022 - Google Patents

Performance evaluation of ai assisted automotive diabetic retinopathy classification systems

Poranki et al., 2022

Document ID
13241111442659142736
Author
Poranki V
Rao B
Publication year
Publication venue
2022 6th International Conference on Electronics, Communication and Aerospace Technology

External Links

Snippet

The reliable diagnosis of diabetic retinopathy (DR) has long been a source of concern for researchers. Due to fluctuating glucose levels, the blood vessels in the retina are more vulnerable to aberrant metabolism. These variances result in lesions or retinal damage …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • 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
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
    • 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
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • 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
    • 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
    • G06K9/00597—Acquiring or recognising eyes, e.g. iris verification
    • 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
    • G06T2207/10072—Tomographic images
    • G06T2207/10101—Optical tomography; Optical coherence tomography [OCT]
    • 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
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • 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
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Akram et al. Automated detection of exudates and macula for grading of diabetic macular edema
Bilal et al. Survey on recent developments in automatic detection of diabetic retinopathy
Bhati et al. Discriminative kernel convolution network for multi-label ophthalmic disease detection on imbalanced fundus image dataset
Zulfira et al. Segmentation technique and dynamic ensemble selection to enhance glaucoma severity detection
Singh et al. A novel multimodality based dual fusion integrated approach for efficient and early prediction of glaucoma
Muangnak et al. Automatic optic disk detection in retinal images using hybrid vessel phase portrait analysis
Kaur et al. A method of disease detection and segmentation of retinal blood vessels using fuzzy C-means and neutrosophic approach
Sakthivel et al. An automated detection of glaucoma using histogram features
Phridviraj et al. A bi-directional Long Short-Term Memory-based Diabetic Retinopathy detection model using retinal fundus images
Agrawal et al. A survey on automated microaneurysm detection in diabetic retinopathy retinal images
Tripathi et al. MTCD: Cataract detection via near infrared eye images
Wang et al. Accurate disease detection quantification of iris based retinal images using random implication image classifier technique
Qu et al. A fully automated segmentation and morphometric parameter estimation system for assessing corneal endothelial cell images
Agustin et al. Implementation of data augmentation to improve performance CNN method for detecting diabetic retinopathy
Pendekal et al. An ensemble classifier based on individual features for detecting microaneurysms in diabetic retinopathy
Prentasic et al. Weighted ensemble based automatic detection of exudates in fundus photographs
Li et al. An unsupervised retinal vessel extraction and segmentation method based on a tube marked point process model
Shojaeipour et al. Using image processing methods for diagnosis diabetic retinopathy
Poranki et al. Performance evaluation of ai assisted automotive diabetic retinopathy classification systems
Khan et al. Screening fundus images to extract multiple ocular features: A unified modeling approach
Wasekar et al. Machine learning for diabetic retinopathy detection using image processing
Lamba et al. State-of-art review on automated glaucoma detection using machine learning techniques
Taş et al. Detection of retinal diseases from ophthalmological images based on convolutional neural network architecture.
Gupta et al. A survey on methods of Automatic Detection of Diabetic Retinopathy
Sharma et al. Blood vessel segmentation using SegNet