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[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 …
Review on deep learning-based CAD systems for breast cancer diagnosis
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 …
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
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 …
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …
Multi-view information fusion in mammograms: A comprehensive overview
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 …
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
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 …
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
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 …
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
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 …
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 …
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
Masses are mammographic nonpalpable signs of breast cancer. These masses could be
detected using screening mammography. This paper proposed a system utilizing orthogonal …
detected using screening mammography. This paper proposed a system utilizing orthogonal …
Disease detection in tomato leaves using machine learning and statistical feature fusion
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 …
diseases. Among the diseases that affect tomato plants, often the type and cause of the …