Zhennan Yan

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Accurate segmentation of whole brain MR images including the cortex, white matter and subcortical structures is challenging due to inter-subject variability and the complex geometry of brain anatomy. However a precise solution would enable accurate, objective measurement of structure volumes for disease quantification. Our contribution is threefold. First(More)
Detecting deception in interpersonal dialog is challenging since deceivers take advantage of the give-and-take of interaction to adapt to any sign of skepticism in an interlocutor's verbal and nonverbal feedback. Human detection accuracy is poor, often with no better than chance performance. In this investigation, we consider whether automated methods can(More)
Automatic medical image analysis systems often start from identifying the human body part contained in the image; Specifically, given a transversal slice, it is important to know which body part it comes from, namely "slice-based bodypart recognition". This problem has its unique characteristic--the body part of a slice is usually identified by local(More)
Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver(More)
Accurate localization of the anatomical landmarks on distal femur bone in the 3D medical images is very important for knee surgery planning and biomechanics analysis. However , the landmark identification process is often conducted manually or by using the inserted auxiliaries, which is time-consuming and lacks of accuracy. In this paper, an automatic(More)
The thigh inter-muscular adipose tissue (IMAT) quantifi-cation plays a critical role in various medical analysis tasks, e.g., the analysis of physical performance or the diagnose of knee osteoarthritis. In recent years, several techniques have been proposed to perform automated thigh tissues quantifi-cation. However, nobody has provided effective methods to(More)
Segmenting structure-of-interest is a fundamental problem in medical image analysis. Numerous automatic segmentation algorithms have been extensively studied for the task. However, misleading image information and the complex organ structures with high curvature boundaries may cause under-or over-segmentation for the deformable models. Learning based(More)
This paper presents a framework to reconstruct mouse left ventricular motion based on tagged MRI using nonlinear Laplacian deformable models, which perform better in terms of accuracy and efficiency. Based on the deformation results, we analyze the LV 3D motion and strain of the myocardial wall to depict the contractile function of the heart. In our(More)
In medical diagnosis, use of elastography is becoming increasingly more useful. However, treatments usually assume a planar compression applied to tissue surfaces and measure the deformation. The stress distribution is relatively uniform close to the surface when using a large, flat compressor but it diverges gradually along tissue depth. Generally in(More)