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Research progress and challenges of deep learning in medical image registration / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 677-683, 2019.
Artículo en Chino | WPRIM | ID: wpr-774155
ABSTRACT
With the development of image-guided surgery and radiotherapy, the demand for medical image registration is stronger and the challenge is greater. In recent years, deep learning, especially deep convolution neural networks, has made excellent achievements in medical image processing, and its research in registration has developed rapidly. In this paper, the research progress of medical image registration based on deep learning at home and abroad is reviewed according to the category of technical methods, which include similarity measurement with an iterative optimization strategy, direct estimation of transform parameters, etc. Then, the challenge of deep learning in medical image registration is analyzed, and the possible solutions and open research are proposed.
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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Investigación / Procesamiento de Imagen Asistido por Computador / Diagnóstico por Imagen / Redes Neurales de la Computación / Aprendizaje Profundo Tipo de estudio: Estudio diagnóstico Idioma: Chino Revista: Journal of Biomedical Engineering Año: 2019 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Investigación / Procesamiento de Imagen Asistido por Computador / Diagnóstico por Imagen / Redes Neurales de la Computación / Aprendizaje Profundo Tipo de estudio: Estudio diagnóstico Idioma: Chino Revista: Journal of Biomedical Engineering Año: 2019 Tipo del documento: Artículo