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Breast cancer detection using deep learning: Datasets, methods, and challenges ahead
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
Reinforcement learning in healthcare: A survey
As a subfield of machine learning, reinforcement learning (RL) aims at optimizing decision
making by using interaction samples of an agent with its environment and the potentially …
making by using interaction samples of an agent with its environment and the potentially …
Reinforcement learning for intelligent healthcare applications: A survey
Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …
Deep reinforcement learning in medical imaging: A literature review
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …
learns a sequence of actions that maximizes the expected reward, with the representative …
Evaluating reinforcement learning agents for anatomical landmark detection
Automatic detection of anatomical landmarks is an important step for a wide range of
applications in medical image analysis. Manual annotation of landmarks is a tedious task …
applications in medical image analysis. Manual annotation of landmarks is a tedious task …
Autonomous navigation of an ultrasound probe towards standard scan planes with deep reinforcement learning
Autonomous ultrasound (US) acquisition is an important yet challenging task, as it involves
interpretation of the highly complex and variable images and their spatial relationships. In …
interpretation of the highly complex and variable images and their spatial relationships. In …
Multiple landmark detection using multi-agent reinforcement learning
The detection of anatomical landmarks is a vital step for medical image analysis and
applications for diagnosis, interpretation and guidance. Manual annotation of landmarks is a …
applications for diagnosis, interpretation and guidance. Manual annotation of landmarks is a …
Image-guided navigation of a robotic ultrasound probe for autonomous spinal sonography using a shadow-aware dual-agent framework
Ultrasound (US) imaging is commonly used to assist in the diagnosis and interventions of
spine diseases, while the standardized US acquisitions performed by manually operating …
spine diseases, while the standardized US acquisitions performed by manually operating …
Deep reinforcement learning techniques in diversified domains: a survey
There have been tremendous improvements in deep learning and reinforcement learning
techniques. Automating learning and intelligence to the full extent remains a challenge. The …
techniques. Automating learning and intelligence to the full extent remains a challenge. The …