Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter

2019 ◽  
pp. 77-102
Author(s):  
Ju Zhang ◽  
Yun Cheng
Keyword(s):  
Guided Filter ◽  
Ultrasonic Images

Speckle filtering of medical ultrasonic images using wavelet and guided filter

Ultrasonics ◽  
2016 ◽  
Vol 65 ◽  
pp. 177-193 ◽  
Author(s):  
Ju Zhang ◽  
Guangkuo Lin ◽  
Lili Wu ◽  
Yun Cheng
Keyword(s):  
Guided Filter ◽  
Speckle Filtering ◽  
Ultrasonic Images

Discrimination of Breast Tumors in Ultrasonic Images by Classifier Ensemble Trained with AdaBoost

2009 ◽  
Vol 129 (4) ◽  
pp. 620-629
Author(s):  
Atsushi Takemura ◽  
Akinobu Shimizu ◽  
Kazuhiko Hamamoto
Keyword(s):  
Breast Tumors ◽  
Classifier Ensemble ◽  
Ultrasonic Images

Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation

2019 ◽  
Vol 12 (3) ◽  
pp. 263-269
Author(s):  
Liu Xian-Hong ◽  
Chen Zhi-Bin
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Filter Bank ◽  
Guided Filter ◽  
Fusion Method ◽  
Edge Preserving ◽  
Directional Information ◽  
Multi Scale ◽  
Directional Filter ◽  
Image Fusion Method

Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter. Methods: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously. Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

A new technique for guided filter based image denoising using modified cuckoo search optimization

2021 ◽  
Vol 176 ◽  
pp. 114884
Author(s):  
Himanshu Singh ◽  
Sethu Venkata Raghavendra Kommuri ◽  
Anil Kumar ◽  
Varun Bajaj
Keyword(s):  
Image Denoising ◽  
Cuckoo Search ◽  
New Technique ◽  
Guided Filter ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
A New Technique

Flaw Detection from Ultrasonic Images using YOLO and SSD

2019 ◽  
Author(s):  
Luka Posilovic ◽  
Duje Medak ◽  
Marko Subasic ◽  
Tomislav Petkovic ◽  
Marko Budimir ◽  
...  
Keyword(s):  
Flaw Detection ◽  
Ultrasonic Images

scholarly journals ResCaps: an improved capsule network and its application in ultrasonic image classification of thyroid papillary carcinoma

2021 ◽  
Author(s):  
Xiongzhi Ai ◽  
Jiawei Zhuang ◽  
Yonghua Wang ◽  
Pin Wan ◽  
Yu Fu
Keyword(s):  
Papillary Carcinoma ◽  
Network Model ◽  
Reliability And Validity ◽  
Thyroid Papillary Carcinoma ◽  
Data Set ◽  
Ultrasonic Image ◽  
First Choice ◽  
Thyroid Papillary ◽  
Ultrasonic Images

AbstractUltrasonic image examination is the first choice for the diagnosis of thyroid papillary carcinoma. However, there are some problems in the ultrasonic image of thyroid papillary carcinoma, such as poor definition, tissue overlap and low resolution, which make the ultrasonic image difficult to be diagnosed. Capsule network (CapsNet) can effectively address tissue overlap and other problems. This paper investigates a new network model based on capsule network, which is named as ResCaps network. ResCaps network uses residual modules and enhances the abstract expression of the model. The experimental results reveal that the characteristic classification accuracy of ResCaps3 network model for self-made data set of thyroid papillary carcinoma was $$81.06\%$$ 81.06 % . Furthermore, Fashion-MNIST data set is also tested to show the reliability and validity of ResCaps network model. Notably, the ResCaps network model not only improves the accuracy of CapsNet significantly, but also provides an effective method for the classification of lesion characteristics of thyroid papillary carcinoma ultrasonic images.

Color image detail enhancement based on quaternion guided filter

2017 ◽  
Vol 24 (4) ◽  
pp. 40-50 ◽  
Author(s):  
Wu Kun ◽  
Li Guiju ◽  
Han Guangliang ◽  
Yang Hang ◽  
Liu Peixun
Keyword(s):  
Color Image ◽  
Guided Filter ◽  
Image Detail ◽  
Detail Enhancement

A Novel Despeckling Method for Medical Ultrasound Images Based on the Nonsubsampled Shearlet and Guided Filter

2019 ◽  
Vol 39 (3) ◽  
pp. 1449-1470 ◽  
Author(s):  
Ju Zhang ◽  
Xiaojie Xiu ◽  
Jun Zhou ◽  
Kailun Zhao ◽  
Zheng Tian ◽  
...  
Keyword(s):  
Guided Filter ◽  
Ultrasound Images ◽  
Medical Ultrasound
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