Y
Yefeng Zheng
Researcher at Tencent
Publications - 473
Citations - 12714
Yefeng Zheng is an academic researcher from Tencent. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 48, co-authored 373 publications receiving 8987 citations. Previous affiliations of Yefeng Zheng include Southeast University & National Research Council.
Papers
More filters
Patent
Image processing using random forest classifiers
Alexey Tsymbal,Michael Kelm,Maria Jimena Costa,Shaohua Kevin Zhou,Dorin Comaniciu,Yefeng Zheng,Alexander G. Schwing +6 more
TL;DR: In this article, a method of performing image retrieval includes training a random forest RF classifier based on low-level features of training images and a high-level feature, using similarity values generated by the RF classifiers to determine a subset of the training images that are most similar to one another, and classifying input images for the high level feature using the random forest classifier and the determined subset of images.
Patent
Method and System for Shape-Constrained Aortic Valve Landmark Detection
TL;DR: In this paper, a rigid global shape defining initial positions of a plurality of aortic valve landmarks is detected within a 3D image, and each of the plurality is detected based on the initial positions.
Journal ArticleDOI
Automatic and efficient contrast-based 2-D/3-D fusion for trans-catheter aortic valve implantation (TAVI)
Rui Liao,Shun Miao,Yefeng Zheng +2 more
TL;DR: A fully automatic and efficient system for contrast-based 2-D/3-D fusion for TAVI by integrating the information of aorta segmentation and aortic landmark detection into intensity-based registration, which combines the merits of intensity- based registration and feature/landmark-basedRegistration.
Book ChapterDOI
Learning-Based Detection and Tracking in Medical Imaging: A Probabilistic Approach
Yang Wang,Bogdan Georgescu,Terrence Chen,Wen Wu,Peng Wang,Xiaoguang Lu,Razvan Ioan Ionasec,Yefeng Zheng,Dorin Comaniciu +8 more
TL;DR: This chapter presents a probabilistic framework that relies on anatomically indexed component-based object models which integrate several sources of information to determine the temporal trajectory of the deformable target and demonstrates various medical image analysis applications with focus on cardiology.
Patent
System and method for detecting an object in a high dimensional space
TL;DR: In this article, a system and method for detecting an object in a high dimensional image space is disclosed, where a first classifier is trained in the marginal space of the object center location which generates a predetermined number of candidate object center locations.