Classification of breast cancer from histopathology images using an ensemble of deep multiscale networks
Manual delineation of tumours in breast histopathology images is generally time-consuming
and laborious. Computer-aided detection systems can assist pathologists by detecting …
and laborious. Computer-aided detection systems can assist pathologists by detecting …
A deep learning method for breast cancer classification in the pathology images
Objective: Breast cancer is the most common female cancer in the world, and it poses a
huge threat to women's health. There is currently promising research concerning its early …
huge threat to women's health. There is currently promising research concerning its early …
Classification of breast tumors based on histopathology images using deep features and ensemble of gradient boosting methods
MR Abbasniya, SA Sheikholeslamzadeh… - Computers and …, 2022 - Elsevier
Breast cancer is the most common cancer among women worldwide. Early-stage diagnosis
of this disease can significantly improve the efficiency of treatment. Computer-Aided …
of this disease can significantly improve the efficiency of treatment. Computer-Aided …
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
Detection and classification of histopathological breast images using a fusion of CNN frameworks
A Rafiq, A Chursin, W Awad Alrefaei… - Diagnostics, 2023 - mdpi.com
Breast cancer is responsible for the deaths of thousands of women each year. The diagnosis
of breast cancer (BC) frequently makes the use of several imaging techniques. On the other …
of breast cancer (BC) frequently makes the use of several imaging techniques. On the other …
[PDF][PDF] Deep learning models combining for breast cancer histopathology image classification
Breast cancer is one of the foremost reasons of death among women in the world. It has the
largest mortality rate compared to the types of cancer accounting for 1.9 million per year in …
largest mortality rate compared to the types of cancer accounting for 1.9 million per year in …
3PCNNB-net: Three parallel CNN branches for breast cancer classification through histopathological images
AM Ibraheem, KH Rahouma, HFA Hamed - Journal of Medical and …, 2021 - Springer
Purpose Diagnosis of breast tumors using histopathological imaging is considered a difficult
task. Oncologists may have different opinions on how to use this imaging technique to …
task. Oncologists may have different opinions on how to use this imaging technique to …
Deep learning applied for histological diagnosis of breast cancer
Deep learning, as one of the currently most popular computer science research trends,
improves neural networks, which has more and deeper layers allowing higher abstraction …
improves neural networks, which has more and deeper layers allowing higher abstraction …
Deep convolutional neural networks for breast cancer histology image analysis
Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics
significantly increases the chances of correct treatment and survival, but this process is …
significantly increases the chances of correct treatment and survival, but this process is …
Breast cancer classification using deep learning approaches and histopathology image: A comparison study
Convolutional Neural Network (CNN) models are a type of deep learning architecture
introduced to achieve the correct classification of breast cancer. This paper has a two-fold …
introduced to achieve the correct classification of breast cancer. This paper has a two-fold …