[HTML][HTML] A survey of convolutional neural network in breast cancer
Aims A large number of clinical trials have proved that if breast cancer is diagnosed at an
early stage, it could give patients more treatment options and improve the treatment effect …
early stage, it could give patients more treatment options and improve the treatment effect …
How artificial intelligence is shaping medical imaging technology: A survey of innovations and applications
L Pinto-Coelho - Bioengineering, 2023 - mdpi.com
The integration of artificial intelligence (AI) into medical imaging has guided in an era of
transformation in healthcare. This literature review explores the latest innovations and …
transformation in healthcare. This literature review explores the latest innovations and …
TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages
S Maqsood, R Damaševičius, R Maskeliūnas - Applied Sciences, 2022 - mdpi.com
Breast cancer is a major research area in the medical image analysis field; it is a dangerous
disease and a major cause of death among women. Early and accurate diagnosis of breast …
disease and a major cause of death among women. Early and accurate diagnosis of breast …
An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images
Breast cancer is the second major reason of death among women around the world. Early
and accurate breast cancer detection is important for proper treatment planning to save a …
and accurate breast cancer detection is important for proper treatment planning to save a …
Automated breast cancer detection in mammography using ensemble classifier and feature weighting algorithms
Breast cancer exhibits one of the highest incidence and mortality rates among all cancers
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
Mammography and ultrasound based dual modality classification of breast cancer using a hybrid deep learning approach
Traditional methods of diagnosing breast cancer (BC) suffer from human errors, are less
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
Currently, most mask extraction techniques are based on convolutional neural networks
(CNNs). However, there are still numerous problems that mask extraction techniques need …
(CNNs). However, there are still numerous problems that mask extraction techniques need …
Breast cancer screening based on supervised learning and multi-criteria decision-making
On average, breast cancer kills one woman per minute. However, there are more reasons
for optimism than ever before. When diagnosed early, patients with breast cancer have a …
for optimism than ever before. When diagnosed early, patients with breast cancer have a …
Breast cancer diagnosis based on hybrid SqueezeNet and improved chef-based optimizer
Q Huang, H Ding, M Effatparvar - Expert Systems with Applications, 2024 - Elsevier
The most frequent disease in women and the one that accounts for the majority of cancer-
related fatalities in females is breast cancer. An important milestone in breast cancer CAD …
related fatalities in females is breast cancer. An important milestone in breast cancer CAD …
Enhancing ductal carcinoma classification using transfer learning with 3D U-net models in breast cancer imaging
Breast cancer ranks among the leading causes of death for women globally, making it
imperative to swiftly and precisely detect the condition to ensure timely treatment and …
imperative to swiftly and precisely detect the condition to ensure timely treatment and …