Efficient compression of images while preserving image quality has the potential to be a major enabler of effective remote clinical diagnosis and treatment, since poor Internet connection conditions are often the primary constraint in such services. This paper presents a framework for organ-specific image compression for teleinterventions based on a deep learning approach and anisotropic diffusion filter.

中文翻译：

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通过 CNN 和各向异性扩散为远程干预有效压缩 3D 医学图像

在保持图像质量的同时有效压缩图像有可能成为有效的远程临床诊断和治疗的主要推动者，因为较差的互联网连接条件通常是此类服务的主要限制因素。本文提出了一种基于深度学习方法和各向异性扩散滤波器的远程干预器官特定图像压缩框架。