[HTML][HTML] Deep learning in mammography images segmentation and classification: Automated CNN approach

WM Salama, MH Aly - Alexandria Engineering Journal, 2021 - Elsevier
In this work, a new framework for breast cancer image segmentation and classification is
proposed. Different models including InceptionV3, DenseNet121, ResNet50, VGG16 and …

Review on deep learning-based CAD systems for breast cancer diagnosis

S Arun Kumar, S Sasikala - Technology in cancer research & …, 2023 - journals.sagepub.com
Breast Cancer (BC) is a major health issue in women of the age group above 45.
Identification of BC at an earlier stage is important to reduce the mortality rate. Image-based …

Deep learning empowered breast cancer diagnosis: Advancements in detection and classification

J Ahmad, S Akram, A Jaffar, Z Ali, SM Bhatti, A Ahmad… - Plos one, 2024 - journals.plos.org
Recent advancements in AI, driven by big data technologies, have reshaped various
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …

Multi-view information fusion in mammograms: A comprehensive overview

A Jouirou, A Baâzaoui, W Barhoumi - Information Fusion, 2019 - Elsevier
In the framework of computer-aided diagnosis of breast cancer, many systems were
designed for the detection, the classification and/or the content-based mammogram retrieval …

Neural networks model based on an automated multi-scale method for mammogram classification

L **e, L Zhang, T Hu, H Huang, Z Yi - Knowledge-Based Systems, 2020 - Elsevier
Breast cancer is the most commonly diagnosed cancer among women. Convolutional neural
networks (CNN)-based mammogram classification plays a vital role in early breast cancer …

Enhanced Alzheimer's disease classification using multilayer deep convolutional neural network-based experimentations

SA Kumar, S Sasikala - Iranian Journal of Science and Technology …, 2023 - Springer
Alzheimer's disease (AD) is an advanced neurological disorder and the main cause of
dementia in the elderly. Early detection of AD is critical for preventing brain damage and …

Detection of breast cancer using fusion of MLO and CC view features through a hybrid technique based on binary firefly algorithm and optimum-path forest classifier

S Sasikala, M Ezhilarasi, S Arun Kumar - Applied Nature-Inspired …, 2020 - Springer
Breast cancer is a leading killer disease among women of the new era. As per the
GLOBOCAN project, the breast cancer incidences showed an increase from 22.2 to 27 …

Towards improving breast cancer detection in ultrasound images using deep transfer learning

V Yamuna, M Monika, RR Amrisha… - … on Advancements in …, 2023 - ieeexplore.ieee.org
Breast Cancer is a serious health issue that affects women all over the globe, and early
detection of it is essential for effective treatment and better patient outcomes. Breast cancer …

Fusion of orthogonal moment features for mammographic mass detection and diagnosis

MWA El-Soud, I Zyout, KM Hosny, MM Eltoukhy - IEEE Access, 2020 - ieeexplore.ieee.org
Masses are mammographic nonpalpable signs of breast cancer. These masses could be
detected using screening mammography. This paper proposed a system utilizing orthogonal …

Disease detection in tomato leaves using machine learning and statistical feature fusion

SA Kumar, S Sasikala - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
Tomato is a domestic plant that is predominantly used worldwide and less tolerant to
diseases. Among the diseases that affect tomato plants, often the type and cause of the …