Convolutional neural networks for breast cancer detection in mammography: A survey
Despite its proven record as a breast cancer screening tool, mammography remains labor-
intensive and has recognized limitations, including low sensitivity in women with dense …
intensive and has recognized limitations, including low sensitivity in women with dense …
Mammogram breast cancer CAD systems for mass detection and classification: a review
Although there is an improvement in breast cancer detection and classification (CAD) tools,
there are still some challenges and limitations that need more investigation. The significant …
there are still some challenges and limitations that need more investigation. The significant …
Connected-UNets: a deep learning architecture for breast mass segmentation
Breast cancer analysis implies that radiologists inspect mammograms to detect suspicious
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …
Annotation-efficient deep learning for automatic medical image segmentation
Automatic medical image segmentation plays a critical role in scientific research and
medical care. Existing high-performance deep learning methods typically rely on large …
medical care. Existing high-performance deep learning methods typically rely on large …
Swin-umamba: Mamba-based unet with imagenet-based pretraining
Accurate medical image segmentation demands the integration of multi-scale information,
spanning from local features to global dependencies. However, it is challenging for existing …
spanning from local features to global dependencies. However, it is challenging for existing …
Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Contour-enhanced attention CNN for CT-based COVID-19 segmentation
Accurate detection of COVID-19 is one of the challenging research topics in today's
healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for …
healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for …
Multi-modal retinal image classification with modality-specific attention network
Recently, automatic diagnostic approaches have been widely used to classify ocular
diseases. Most of these approaches are based on a single imaging modality (eg, fundus …
diseases. Most of these approaches are based on a single imaging modality (eg, fundus …