A Generalized Hermite Pyramid for Ultrasonic Image Analysis I. Kidney and Liver

1996 ◽  
Vol 18 (4) ◽  
pp. 261-304 ◽  
Author(s):  
Y. V. Venkatesh
Keyword(s):  
Image Analysis ◽  
Multiscale Analysis ◽  
Tissue Characterization ◽  
Medical Doctor ◽  
Physical Characteristics ◽  
Gray Level ◽  
Diagnostic Aid ◽  
Ultrasonic Image ◽  
Homogeneous Groups ◽  
Ultrasonic Images

Ultrasonic images of the kidney and of the liver are subjected to a multiscale analysis in a generalized Hermite pyramid framework. The gradient images of the multiscale decompositions of the images of healthy and sick kidneys, and of the intraoperative and conventionally imaged livers, exhibit differences, in the structures of gray level regions, which can be interpreted by a medical doctor. These are used as inputs to an unsupervised classifier to automatically classify the images into homogeneous groups, which are found, in the case of the ultrasonic images examined, to correspond to the different physical characteristics of tissues of the organs under study. The main contribution of the paper is believed to be the multiscale tissue characterization along with its display in a manner that has utility as a diagnostic aid to the clinician.

A Generalized Hermite Pyramid for Ultrasonic Image Analysis II. Gallstones

1996 ◽  
Vol 18 (4) ◽  
pp. 305-327
Author(s):  
Y. V. Venkatesh
Keyword(s):  
Image Analysis ◽  
Chemical Composition ◽  
Ultrasonic Imaging ◽  
Decomposition Technique ◽  
Human Gallbladder ◽  
Ultrasonic Image ◽  
Ultrasonic Images

This paper deals with the problem of extracting information regarding the chemical composition of stones in the human gallbladder from in vitro and in vivo B-scan ultrasonic images. The images are subjected to the Hermite pyramid decomposition technique described in Part I (Venkatesh, Y. V., Ultrasonic Imaging, 18, 261–304, 1996). In an attempt to determine the chemical composition of the gallstones, the gradients of the decomposed images are input to an unsupervised classifier. The outputs of the classifier exhibit some interesting patterns that appear to be related to the chemical composition of the gallstones contained in these 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.

Evaluation of ImageJ software in ultrasonic image analysis: follicular and luteal morphological characteristics of cattle

2021 ◽  
pp. 106907
Author(s):  
Lindomar Sousa Brito ◽  
Ana Karina da Silva Cavalcante ◽  
Alexandra Soares Rodrigues ◽  
Priscila Assis Ferraz ◽  
Rodrigo Freitas Bittencourt ◽  
...  
Keyword(s):  
Image Analysis ◽  
Morphological Characteristics ◽  
Ultrasonic Image ◽  
Imagej Software

A Robust Line Filter for Automatic X-Ray/CT Image Segmentation

2014 ◽  
Vol 721 ◽  
pp. 783-787
Author(s):  
Shao Hu Peng ◽  
Hyun Do Nam ◽  
Yan Fen Gan ◽  
Xiao Hu
Keyword(s):  
Multiscale Analysis ◽  
Automatic Segmentation ◽  
Local Variation ◽  
Recognition System ◽  
Ct Images ◽  
Gray Level ◽  
Ct Image ◽  
Image Pyramid ◽  
Level Variation ◽  
X Ray

Automatic segmentation of the line-like regions plays a very important role in the automatic recognition system, such as automatic cracks recognition in X-ray images, automatic vessels segmentation in CT images. In order to automatically segment line-like regions in the X-ray/CT images, this paper presents a robust line filter based on the local gray level variation and multiscale analysis. The proposed line filter makes usage of the local gray level and its local variation to enhance line-like regions in the X-ray/CT image, which can well overcome the problems of the image noises and non-uniform intensity of the images. For detecting various sizes of line-like regions, an image pyramid is constructed based on different neighboring distances, which enables the proposed filter to analyze different sizes of regions independently. Experimental results showed that the proposed line filter can well segment various sizes of line-like regions in the X-ray/CT images, which are with image noises and non-uniform intensity problems.

An Image Analysis Workstation for Ultrasonic Tissue Characterization

1985 ◽  
pp. 491-495
Author(s):  
D. Schlaps ◽  
U. Räth ◽  
J. F. Volk ◽  
I. Zuna ◽  
A. Lorenz ◽  
...  
Keyword(s):  
Image Analysis ◽  
Tissue Characterization

Ultrasonic Tissue Characterization with Gray Level Histogram Width

2013 ◽  
pp. 17-17
Author(s):  
Kazuo Maeda ◽  
Masaji Utsu ◽  
Nobuhiro Yamamoto ◽  
Mariko Serizawa
Keyword(s):  
Tissue Characterization ◽  
Gray Level ◽  
Gray Level Histogram

Ultrasonic image analysis for beef tenderness

1993 ◽  
Author(s):  
Bosoon Park ◽  
Brian R. Thane ◽  
A. D. Whittaker
Keyword(s):  
Image Analysis ◽  
Beef Tenderness ◽  
Ultrasonic Image

Formalization and computational aspects of image analysis

Acta Numerica ◽  
1994 ◽  
Vol 3 ◽  
pp. 1-59 ◽  
Author(s):  
Luis Alvarez ◽  
Jean Michel Morel
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Image Analysis ◽  
Image Segmentation ◽  
Multiscale Analysis ◽  
Parabolic Differential Equation ◽  
The Past ◽  
Computational Aspects ◽  
Shape Analyses ◽  
New Algorithms

In this article we shall present a unified and axiomatized view of several theories and algorithms of image multiscale analysis (and low level vision) which have been developed in the past twenty years. We shall show that under reasonable invariance and assumptions, all image (and shape) analyses can be reduced to a single partial differential equation. In the same way, movie analysis leads to a single parabolic differential equation. We discuss some applications to image segmentation and movie restoration. The experiments show how accurate and invariant the numerical schemes must be and we compare several (old and new) algorithms by discussing how well they match the axiomatic invariance requirements.

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