Breast tumor classification in ultrasound images using combined deep and handcrafted features
This study aims to enable effective breast ultrasound image classification by combining
deep features with conventional handcrafted features to classify the tumors. In particular, the …
deep features with conventional handcrafted features to classify the tumors. In particular, the …
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 …
Classification of breast cancer lesions in ultrasound images by using attention layer and loss ensemble in deep convolutional neural networks
The reliable classification of benign and malignant lesions in breast ultrasound images can
provide an effective and relatively low-cost method for the early diagnosis of breast cancer …
provide an effective and relatively low-cost method for the early diagnosis of breast cancer …
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 …
Breast tumor classification in ultrasound images by fusion of deep convolutional neural network and shallow LBP feature
H Chen, M Ma, G Liu, Y Wang, Z Jin, C Liu - Journal of digital imaging, 2023 - Springer
Breast cancer is one of the most dangerous and common cancers in women which leads to
a major research topic in medical science. To assist physicians in pre-screening for breast …
a major research topic in medical science. To assist physicians in pre-screening for breast …
Breast ultrasound lesion classification based on image decomposition and transfer learning
Z Zhuang, Y Kang, AN Joseph Raj, Y Yuan… - Medical …, 2020 - Wiley Online Library
Purpose In medical image analysis, deep learning has great application potential.
Discovering a method for extracting valuable information from medical images and …
Discovering a method for extracting valuable information from medical images and …
Deep learning technique for classification of breast cancer using ultrasound images
M Zourhri, S Hamida, N Akouz… - … Research in Applied …, 2023 - ieeexplore.ieee.org
Breast cancer is a significant medical and social issue that draws attention from the global
scientific community. The classification of ultrasound images of breast cancer plays a crucial …
scientific community. The classification of ultrasound images of breast cancer plays a crucial …
A novel approach with dual-sampling convolutional neural network for ultrasound image classification of breast tumors
J Xie, X Song, W Zhang, Q Dong, Y Wang… - Physics in Medicine & …, 2020 - iopscience.iop.org
Breast cancer is one of the leading causes of female cancer deaths. Early diagnosis with
prophylactic may improve the patients' prognosis. So far ultrasound (US) imaging has been …
prophylactic may improve the patients' prognosis. So far ultrasound (US) imaging has been …
Achieving highly efficient breast ultrasound tumor classification with deep convolutional neural networks
Ultrasound imaging is one of the common modalities used nowadays during radiological
screening of breast cancer. A novel residual deep convolutional neural network (DCNN) is …
screening of breast cancer. A novel residual deep convolutional neural network (DCNN) is …
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 …