Z
Zhijian Song
Researcher at Fudan University
Publications - 69
Citations - 1133
Zhijian Song is an academic researcher from Fudan University. The author has contributed to research in topics: Computer science & Image registration. The author has an hindex of 14, co-authored 46 publications receiving 741 citations.
Papers
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Journal ArticleDOI
Computer-aided detection in chest radiography based on artificial intelligence: a survey
TL;DR: The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography.
Journal ArticleDOI
Easy-to-use augmented reality neuronavigation using a wireless tablet PC.
TL;DR: A easy-to-use Tablet-AR system that transmits navigation information to a movable tablet PC via a wireless local area network and overlays this information on the tablet screen, which simultaneously displays the actual scene captured by its back-facing camera.
Journal ArticleDOI
Classification and analysis of the errors in neuronavigation.
Manning Wang,Zhijian Song +1 more
TL;DR: The classification and analysis of these errors should help neurosurgeons understand the power and limits of neuronavigation systems and use them more properly.
Book ChapterDOI
Efficient Global Point Cloud Registration by Matching Rotation Invariant Features Through Translation Search
TL;DR: This paper decouple the optimization of translation and rotation, and proposes a fast BnB algorithm to globally optimize the 3D translation parameter first and demonstrates that the proposed method outperforms state-of-the-art global methods in terms of both speed and accuracy.
Journal ArticleDOI
Organ at Risk Segmentation in Head and Neck CT Images Using a Two-Stage Segmentation Framework Based on 3D U-Net
TL;DR: In this article, a two-stage segmentation framework based on 3D U-Net is proposed for organs at risk (OARs) segmentation, where the segmentation of each OAR is decomposed into two subtasks.