Deep learning-enabled medical computer vision
Медицинское компьютерное зрение на основе глубокого обучения
2021-01-08
SCID: 54.1/w9k4bqj9
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clinical deploymentconvolutional neural networksdeep learning-enabled medical computer visionmedical imagingmedical video
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Abstract (AI)
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques-powered by deep learning-for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit-including cardiology, pathology, dermatology, ophthalmology-and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.
Key Findings
1
Convolutional neural networks enable a range of vision tasks relevant to healthcare and have been central to recent advances in medical computer vision.
2
Deep learning-powered computer vision has made substantial progress over the past decade with direct applicability to medical imaging, medical video, and clinical deployment.
3
Integration of computer vision into clinical workflows for medical video can enhance care, suggesting practical applications beyond static medical imaging.
4
Medical specialties likely to benefit from these techniques include cardiology, pathology, dermatology, and ophthalmology, with proposed avenues for further work in each area.
5
Significant challenges and hurdles remain for real-world clinical deployment of deep learning computer vision technologies, requiring further attention.
Research Object
Deep learning-enabled medical computer vision systems (medical imaging and medical video applications)
Research Subject
Application and development of deep learning computer-vision techniques for medical tasks, including imaging and video diagnostics, clinical workflow integration, and challenges for real-world clinical deployment
Publication Details
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2021-01-08
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