Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Attention dense-u-net for automatic breast mass segmentation in digital mammogram
S Li, M Dong, G Du, X Mu - Ieee Access, 2019 - ieeexplore.ieee.org
Breast mass is one of the most distinctive signs for the diagnosis of breast cancer, and the
accurate segmentation of masses is critical for improving the accuracy of breast cancer …
accurate segmentation of masses is critical for improving the accuracy of breast cancer …
Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
[HTML][HTML] Deep learning in mammography images segmentation and classification: Automated CNN approach
In this work, a new framework for breast cancer image segmentation and classification is
proposed. Different models including InceptionV3, DenseNet121, ResNet50, VGG16 and …
proposed. Different models including InceptionV3, DenseNet121, ResNet50, VGG16 and …
[HTML][HTML] A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks
Breast cancer is currently the second most common cause of cancer-related death in
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
A systematic survey of deep learning in breast cancer
In recent years, we witnessed a speeding development of deep learning in computer vision
fields like categorization, detection, and semantic segmentation. Within several years after …
fields like categorization, detection, and semantic segmentation. Within several years after …
Integrating segmentation information into CNN for breast cancer diagnosis of mammographic masses
L Tsochatzidis, P Koutla, L Costaridou… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objectives Segmentation of mammographic lesions has been
proven to be a valuable source of information, as it can assist in both extracting shape …
proven to be a valuable source of information, as it can assist in both extracting shape …
MRFE-CNN: Multi-route feature extraction model for breast tumor segmentation in Mammograms using a convolutional neural network
R Ranjbarzadeh, N Tataei Sarshar… - Annals of Operations …, 2023 - Springer
Breast cancer is cancer that develops from the breast tissue and has been recognized as
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
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 …
A comprehensive review on breast cancer detection, classification and segmentation using deep learning
The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …