A survey of computer-aided tumor diagnosis based on convolutional neural network
Simple Summary One of the hottest areas in deep learning is computerized tumor diagnosis
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …
Deep feature extraction and classification of breast ultrasound images
Controlled despeckling (structure/edges/feature preservation with smoothing the
homogeneous areas) is a desired pre-processing step for the design of computer-aided …
homogeneous areas) is a desired pre-processing step for the design of computer-aided …
Breast lesion classification in ultrasound images using deep convolutional neural network
B Zeimarani, MGF Costa, NZ Nurani, SR Bianco… - IEEE …, 2020 - ieeexplore.ieee.org
In recent years, convolutional neural networks (CNNs) have found many applications in
medical image analysis. Having enough labeled data, CNNs could be trained to learn image …
medical image analysis. Having enough labeled data, CNNs could be trained to learn image …
Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images
Background The rapid development of artificial intelligence technology has improved the
capability of automatic breast cancer diagnosis, compared to traditional machine learning …
capability of automatic breast cancer diagnosis, compared to traditional machine learning …
Comparison of different CNNs for breast tumor classification from ultrasound images
Breast cancer is one of the deadliest cancer worldwide. Timely detection could reduce
mortality rates. In the clinical routine, classifying benign and malignant tumors from …
mortality rates. In the clinical routine, classifying benign and malignant tumors from …
Deep learning algorithm using bispectrum analysis energy feature maps based on ultrasound radiofrequency signals to detect breast cancer
Q Wang, X Jia, T Luo, J Yu, S Xia - Frontiers in Oncology, 2023 - frontiersin.org
Background Ultrasonography is an important imaging method for clinical breast cancer
screening. As the original echo signals of ultrasonography, ultrasound radiofrequency (RF) …
screening. As the original echo signals of ultrasonography, ultrasound radiofrequency (RF) …
An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images
R Tian, M Yu, L Liao, C Zhang, J Zhao, L Sang… - … Engineering Sciences in …, 2023 - Springer
Breast and thyroid cancers are the two most common cancers among women worldwide.
The early clinical diagnosis of breast and thyroid cancers often utilizes ultrasonography …
The early clinical diagnosis of breast and thyroid cancers often utilizes ultrasonography …
Correlated-weighted statistically modeled contourlet and curvelet coefficient image-based breast tumor classification using deep learning
SM Kabir, MIH Bhuiyan - Diagnostics, 2022 - mdpi.com
Deep learning-based automatic classification of breast tumors using parametric imaging
techniques from ultrasound (US) B-mode images is still an exciting research area. The …
techniques from ultrasound (US) B-mode images is still an exciting research area. The …
RIIG modeled WCP image-based CNN Architecture and feature-based approach in breast tumor classification from B-Mode Ultrasound
This study presents two new approaches based on Weighted Contourlet Parametric (WCP)
images for the classification of breast tumors from B-mode ultrasound images. The Rician …
images for the classification of breast tumors from B-mode ultrasound images. The Rician …
机器学习在超声图像中的应用综述.
徐可文， 许波， 吴英， 徐浩然 - Journal of Computer …, 2021 - search.ebscohost.com
超声图像为临床疾病检测与诊断提供重要的辅助信息, 机器学习在超声图像中的应用给超声图像
的分析诊断带来了新变革. 从超声图像的去噪, 分割, 检测, 分类等方面介绍了超声图像的研究 …
的分析诊断带来了新变革. 从超声图像的去噪, 分割, 检测, 分类等方面介绍了超声图像的研究 …