College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea.
Comput Biol Med. 2013 Oct;43(10):1471-83. doi: 10.1016/j.compbiomed.2013.07.001. Epub 2013 Jul 10.
The objective of the present study is to explore prioritization methods in diagnostic imaging modalities to automatically determine the contents of medical images. In this paper, we propose an efficient prioritization of brain MRI. First, the visual perception of the radiologists is adapted to identify salient regions. Then this saliency information is used as an automatic label for accurate segmentation of brain lesion to determine the scientific value of that image. The qualitative and quantitative results prove that the rankings generated by the proposed method are closer to the rankings created by radiologists.
本研究旨在探讨诊断成像模式中的优先级方法，以自动确定医学图像的内容。在本文中，我们提出了一种有效的脑 MRI 优先级方法。首先，我们使放射科医生的视觉感知适应于识别显著区域。然后，将此显着性信息用作大脑病变的准确分割的自动标签，以确定该图像的科学价值。定性和定量结果证明，所提出的方法生成的排名更接近放射科医生创建的排名。
