Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms
Objective: Mammogram-based automatic breast cancer detection has a primary role in
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
A multimodal breast cancer diagnosis method based on Knowledge-Augmented Deep Learning
D Guo, C Lu, D Chen, J Yuan, Q Duan, Z Xue… - … Signal Processing and …, 2024 - Elsevier
Breast cancer is a worldwide medical challenge that requires Early diagnosis. While there
are numerous diagnostic methods for breast cancer, many primarily focus on network …
are numerous diagnostic methods for breast cancer, many primarily focus on network …
[HTML][HTML] A deep convolutional neural network for the classification of imbalanced breast cancer dataset
The primary procedures for breast cancer diagnosis involve the assessment of
histopathological slide images by skilled patholo-gists. This procedure is prone to human …
histopathological slide images by skilled patholo-gists. This procedure is prone to human …
AWOLSE: Adaptive weight optimized level set evolution-based blood cell segmentation
Proper and precise segmentation of blood cells is a crucial task in the detection of
hematological disorders. The presence of intensity inhomogeneity, noise, and weak edges …
hematological disorders. The presence of intensity inhomogeneity, noise, and weak edges …
An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer
This work proposes an effective sparse-based hybrid alternating deep-layer cascade model
(HADLCM) for breast cancer detection. It is achieved by cascading sparse and collaborative …
(HADLCM) for breast cancer detection. It is achieved by cascading sparse and collaborative …
An efficient deep learning network with orthogonal softmax layer for automatic detection of tuberculosis
PK Das, S Sreevatsav, A Abraham - Engineering Applications of Artificial …, 2024 - Elsevier
Tuberculosis (TB) is a persistent bacterial lung infection that affects the lungs severely. It is
one of the fatal diseases among the top ten leading causes of death. Thus, early and …
one of the fatal diseases among the top ten leading causes of death. Thus, early and …
A Deforestation Detection Network Using Deep Learning-Based Semantic Segmentation
Semantic segmentation is an important task in which the class label of each pixel is
predicted. Thus, it is quite tough compared with classification and classical segmentation …
predicted. Thus, it is quite tough compared with classification and classical segmentation …
Mammo-Light: A lightweight convolutional neural network for diagnosing breast cancer from mammography images
People of all countries, developed and developing alike endure cancer-related fatal
diseases. The rate of breast cancer in females is increasing daily, partly due to ignorance …
diseases. The rate of breast cancer in females is increasing daily, partly due to ignorance …
Integration of ultrasound and mammogram for multimodal classification of breast cancer using hybrid residual neural network and machine learning
Breast cancer (BC) is one of the topmost causes of mortality in women all over the world.
Early detection and classification of the tumor allow proper treatment of patients and …
Early detection and classification of the tumor allow proper treatment of patients and …
Malignancy pattern analysis of breast ultrasound images using clinical features and a graph convolutional network
Objective Early diagnosis of breast cancer can lead to effective treatment, possibly increase
long-term survival rates, and improve quality of life. The objective of this study is to present …
long-term survival rates, and improve quality of life. The objective of this study is to present …