A review on image-based approaches for breast cancer detection, segmentation, and classification
Z Rezaei - Expert Systems with Applications, 2021 - Elsevier
The breast cancer as the most life-threatening disease among the woman has emerged in
the worldwide. It is supposed that the early testing and treatment for breast cancer detection …
the worldwide. It is supposed that the early testing and treatment for breast cancer detection …
SMU-Net: Saliency-guided morphology-aware U-Net for breast lesion segmentation in ultrasound image
Z Ning, S Zhong, Q Feng, W Chen… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Deep learning methods, especially convolutional neural networks, have been successfully
applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern …
applied to lesion segmentation in breast ultrasound (BUS) images. However, pattern …
Methods for the segmentation and classification of breast ultrasound images: a review
Purpose Breast ultrasound (BUS) is one of the imaging modalities for the diagnosis and
treatment of breast cancer. However, the segmentation and classification of BUS images is a …
treatment of breast cancer. However, the segmentation and classification of BUS images is a …
Mammography and ultrasound based dual modality classification of breast cancer using a hybrid deep learning approach
Traditional methods of diagnosing breast cancer (BC) suffer from human errors, are less
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
UNet: A semi-supervised method for segmentation of breast tumor images using a U-shaped pyramid-dilated network
Rapid and precise segmentation of breast tumors is a severe challenge for the global
research community to diagnose breast cancer in younger females. An ultrasound system is …
research community to diagnose breast cancer in younger females. An ultrasound system is …
An RDAU-NET model for lesion segmentation in breast ultrasound images
Breast cancer is a common gynecological disease that poses a great threat to women health
due to its high malignant rate. Breast cancer screening tests are used to find any warning …
due to its high malignant rate. Breast cancer screening tests are used to find any warning …
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 …
Multimodal classification of breast cancer using feature level fusion of mammogram and ultrasound images in machine learning paradigm
The manual examination of Breast Cancer (BC) images for disease detection is prone to
error, is time-consuming, and has low accuracy. The Computer-Aided Detection (CAD) …
error, is time-consuming, and has low accuracy. The Computer-Aided Detection (CAD) …
Superpixel-guided iterative learning from noisy labels for medical image segmentation
Learning segmentation from noisy labels is an important task for medical image analysis
due to the difficulty in acquiring high-quality annotations. Most existing methods neglect the …
due to the difficulty in acquiring high-quality annotations. Most existing methods neglect the …
Pseudo-label refinement using superpixels for semi-supervised brain tumour segmentation
BH Thompson, G Di Caterina… - 2022 IEEE 19th …, 2022 - ieeexplore.ieee.org
Training neural networks using limited annotations is an important problem in the medical
domain. Deep Neural Networks (DNNs) typically require large, annotated datasets to …
domain. Deep Neural Networks (DNNs) typically require large, annotated datasets to …