Kaur et al., 2023 - Google Patents

A complete review on image denoising techniques for medical images.

Kaur et al., 2023

Document ID
14829210870265039240
Author
Kaur A
Dong G
Publication year
Publication venue
Neural Process. Lett.

External Links

Snippet

Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging, are widely used for diagnosis in the healthcare domain. However, these methods are often affected by noise, which can lead to incorrect diagnoses. Radiologists used to rely on visual …
Continue reading at search.proquest.com (other versions)

Classifications

    • 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
    • G06T2207/20048—Transform domain processing
    • G06T2207/20064—Wavelet transform [DWT]
    • 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
    • G06T2207/20048—Transform domain processing
    • G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
    • 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
    • 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
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
    • 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
    • G06T2207/20172—Image enhancement details
    • 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
    • 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
    • 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
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/007—Dynamic range modification
    • G06T5/008—Local, e.g. shadow enhancement
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/001—Image restoration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Kaur et al. A complete review on image denoising techniques for medical images
Thakur et al. State‐of‐art analysis of image denoising methods using convolutional neural networks
Kaderuppan et al. Smart nanoscopy: a review of computational approaches to achieve super-resolved optical microscopy
Yu et al. Two-stage image decomposition and color regulator for low-light image enhancement
Sharma et al. Solving image processing critical problems using machine learning
Guo et al. Low-light image enhancement with joint illumination and noise data distribution transformation
Singh et al. Microscopic biopsy image reconstruction using inception block with denoising auto-encoder approach
Yang et al. LatLRR-CNN: An infrared and visible image fusion method combining latent low-rank representation and CNN
Roy et al. A DCT-based multiscale framework for 2D greyscale image fusion using morphological differential features
Esteki et al. SW/SE-CNN: semi-wavelet and specific image edge extractor CNN for Gaussian image denoising
Lu et al. UNet-Att: a self-supervised denoising and recovery model for two-photon microscopic image
Raj et al. SpFusionNet: deep learning-driven brain image fusion with spatial frequency analysis
Aly et al. Efficient implementation of image fusion and interpolation for brain tumor diagnosis
Guo Real-time medical image denoising and information hiding model based on deep wavelet multiscale autonomous unmanned analysis: G. Guo
Arumugam et al. Integrating multi-scale attention network with deep image prior for single image restoration
Sengan et al. A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images
Han et al. Phase contrast image restoration by formulating its imaging principle and reversing the formulation with deep neural networks
Annaiah et al. Data-driven real-time image super-resolution with enhanced generative adversarial networks
Liu et al. Multi-focused image fusion algorithm based on multi-scale hybrid attention residual network
Gor et al. Self-Supervised Image Denoiser Design Using Multiscale Bicubic Image Interpolation and U-Net Network
Singh et al. A systematic comparative analysis of quantum mechanics-based image processing and denoising algorithms
Annavarapu et al. Figure-ground segmentation based medical image denoising using deep convolutional neural networks
Wieslander et al. TEM image restoration from fast image streams
Mohammed et al. A novel image denoising algorithm based on least square generative adversarial network
Narasimha et al. Integrating Taylor–Krill herd‐based SVM to fuzzy‐based adaptive filter for medical image denoising