Medical volume image summarization
Feng Ding, Hao Li, Yuan Cheng, Wee Kheng Leow · 2009
Medical volume images are large in size. They cannot be efficiently transmitted and visualized as candidates for medical image retrieval and relevance feedback. On the other hand, 2D images that are small in size and rich in 3D details can be efficiently transmitted and visualized as candidates. This paper presents an algorithm that summarizes the 3D details in a volume image into a single 2D image. It applies soft segmentation to highlight the anatomy of interest in the volume, and automatically selects a salient view that contains the most amount of semantic information as the summarization of the volume image. Experimental results show that the proposed method can well summarize medical volume images of different anatomical structures. Compared to representation of volume images using 2D slices and conventional volume rendering, our summarized images are rich in 3D details, and they can be transmitted and visualized very efficiently.