Texture Analysis Based on Auto-Mutual Information for Classifying Breast Lesions with Ultrasound-Reference-Cited by-同舟云学术

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Texture Analysis Based on Auto-Mutual Information for Classifying Breast Lesions with Ultrasound

Published:2019-08 Issue:8 Volume:45 Page:2213-2225
ISSN:0301-5629
Container-title:Ultrasound in Medicine & Biology
language:en
Short-container-title:Ultrasound in Medicine & Biology

Author:

Gómez-Flores Wilfrido,Rodríguez-Cristerna Arturo,de Albuquerque Pereira Wagner Coelho

Funder

National Council of Science and Technology

CONACyT

Publisher

Elsevier BV

Subject

Acoustics and Ultrasonics,Radiology, Nuclear Medicine and imaging,Biophysics,Radiological and Ultrasound Technology

Reference51 articles.

1. Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization;Al-Kadi;Med Image Anal,2015

2. Complexity curve and grey level co-occurrence matrix in the texture evaluation of breast tumor on ultrasound images;Alvarenga;Med Phys,2007

3. Assessing the combined performance of texture and morphological parameters in distinguishing breast tumors in ultrasound images;Alvarenga;Med Phys,2012

4. Breast cancer facts & figures 2015–2016,2015

5. The World Health Organization histological typing of breast tumors—Second edition;Azzopardi;Am J Clin Pathol,1982

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1. BUS‐BRA: A breast ultrasound dataset for assessing computer‐aided diagnosis systems;Medical Physics;2023-11-08

2. Myofascial Trigger Point Identification in B-Mode Ultrasound: Texture Analysis Versus a Convolutional Neural Network Approach;Ultrasound in Medicine & Biology;2023-10

3. Comparison of Texture, Shape, and Combined Feature Vectors for Classification of Breast Ultrasound Images;Recent Advances in Metrology;2023-09-02

4. A Comparison of Ultrasound Imaging Texture Analyses During the Early Postpartum With the Mode of Delivery;Journal of Human Lactation;2022-03-11

5. A Huanglongbing Detection Method for Orange Trees Based on Deep Neural Networks and Transfer Learning;IEEE Access;2022

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