Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021 - Elsevier
Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

NIR Yassin, S Omran, EMF El Houby… - Computer methods and …, 2018 - Elsevier
Background and objective The high incidence of breast cancer in women has increased
significantly in the recent years. Physician experience of diagnosing and detecting breast …

Machine learning in ultrasound computer‐aided diagnostic systems: a survey

Q Huang, F Zhang, X Li - BioMed research international, 2018 - Wiley Online Library
The ultrasound imaging is one of the most common schemes to detect diseases in the
clinical practice. There are many advantages of ultrasound imaging such as safety …

A brief survey on breast cancer diagnostic with deep learning schemes using multi-image modalities

T Mahmood, J Li, Y Pei, F Akhtar, A Imran… - IEEe …, 2020 - ieeexplore.ieee.org
Patients with breast cancer are prone to serious health-related complications with higher
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …

Hyperspectral image super-resolution using deep convolutional neural network

Y Li, J Hu, X Zhao, W **e, JJ Li - Neurocomputing, 2017 - Elsevier
Limited by the existed imagery hardware, it is challenging to obtain a hyperspectral image
(HSI) with a high spatial resolution. Super-resolution (SR) focuses on the ways to enhance …

A systematic literature review of breast cancer diagnosis using machine intelligence techniques

V Nemade, S Pathak, AK Dubey - Archives of Computational Methods in …, 2022 - Springer
Breast cancer is one of the most common diseases in women; it can have long-term
implications and can even be fatal. However, early detection, achieved through recent …

RRCNet: Refinement residual convolutional network for breast ultrasound images segmentation

G Chen, Y Dai, J Zhang - Engineering applications of artificial intelligence, 2023 - Elsevier
Breast ultrasound images segmentation is one of the key steps in clinical auxiliary diagnosis
of breast cancer, which seriously threatens women's health. Currently, deep learning …

[HTML][HTML] A review of machine learning techniques for the classification and detection of breast cancer from medical images

R Jalloul, HK Chethan, R Alkhatib - Diagnostics, 2023 - mdpi.com
Cancer is an incurable disease based on unregulated cell division. Breast cancer is the
most prevalent cancer in women worldwide, and early detection can lower death rates …

Optimal breast cancer classification using Gauss–Newton representation based algorithm

L Dora, S Agrawal, R Panda, A Abraham - Expert Systems with Applications, 2017 - Elsevier
Breast cancer is a decisive disease worldwide. It is one of the most widely spread cancer
among women. As per the survey, one out of eight women in the world are at risk of breast …

Automatic breast lesion segmentation in phase preserved DCE-MRIs

D Pandey, H Wang, X Yin, K Wang, Y Zhang… - … Information Science and …, 2022 - Springer
We offer a framework for automatically and accurately segmenting breast lesions from
Dynamic Contrast Enhanced (DCE) MRI in this paper. The framework is built using max flow …