[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
Advancing pharmacy and healthcare with virtual digital technologies
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally.
From the different technologies, virtual tools including artificial intelligence, blockchain …
From the different technologies, virtual tools including artificial intelligence, blockchain …
Medical image augmentation for lesion detection using a texture-constrained multichannel progressive GAN
Q Guan, Y Chen, Z Wei, AA Heidari, H Hu… - Computers in Biology …, 2022 - Elsevier
Lesion detectors based on deep learning can assist doctors in diagnosing diseases.
However, the performance of current detectors is likely to be unsatisfactory due to the …
However, the performance of current detectors is likely to be unsatisfactory due to the …
TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages
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 …
AAU-net: an adaptive attention U-net for breast lesions segmentation in ultrasound images
Various deep learning methods have been proposed to segment breast lesions from
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
ultrasound images. However, similar intensity distributions, variable tumor morphologies …
Breast cancer diagnosis using optimized deep convolutional neural network based on transfer learning technique and improved Coati optimization algorithm
MM Emam, EH Houssein, NA Samee… - Expert Systems with …, 2024 - Elsevier
Breast cancer is a significant health concern due to its aggressive nature and high mortality
rates. Early detection is crucial to improving patient outcomes. Thermography, a non …
rates. Early detection is crucial to improving patient outcomes. Thermography, a non …
A yolo-based model for breast cancer detection in mammograms
This work aims to implement an automated data-driven model for breast cancer detection in
mammograms to support physicians' decision process within a breast cancer screening or …
mammograms to support physicians' decision process within a breast cancer screening or …
BI-RADS Category Prediction from Mammography Images and Mammography Radiology Reports Using Deep Learning: A Systematic Review
Women's health and mortality are significantly threatened by breast cancer, underscoring
the importance of timely detection and treatment. Mammograms are an extremely useful and …
the importance of timely detection and treatment. Mammograms are an extremely useful and …
C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation
Background and objective Breast lesions segmentation is an important step of computer-
aided diagnosis system. However, speckle noise, heterogeneous structure, and similar …
aided diagnosis system. However, speckle noise, heterogeneous structure, and similar …
Rethinking the unpretentious U-net for medical ultrasound image segmentation
Breast tumor segmentation from ultrasound images is one of the key steps that help us
characterize and localize tumor regions. However, variable tumor morphology, blurred …
characterize and localize tumor regions. However, variable tumor morphology, blurred …