Computational Methods and Clinical Applications for Spine Imaging
4th International Workshop and Challenge, CSI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers
Page
%P
21 Result(s)
within
Computer Science
Artificial Intelligence
Computer Graphics
Image Processing and Computer Vision
Simulation and Modeling
**hu Li
-
Book and Conference Proceedings
-
Book and Conference Proceedings
Computational Methods and Clinical Applications for Spine Imaging
Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings
-
Chapter and Conference Paper
Fully Automatic Localization and Segmentation of Intervertebral Disc from 3D Multi-modality MR Images by Regression Forest and CNN
In this paper, we propose a fully automatic framework to localize and segment intervertebral discs (IVDs) from 3D Multi-modality MR Images. Random forest regression is employed to coarsely localize the IVD. Th...
-
Chapter and Conference Paper
Multi-scale and Modality Dropout Learning for Intervertebral Disc Localization and Segmentation
Automatic localization and segmentation of intervertebral discs (IVDs) from volumetric magnetic resonance (MR) images is important for spine disease diagnosis. It dramatically alleviates the workload of radiol...
-
Chapter and Conference Paper
Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial-Temporal Hypergraph Learning
Accurate segmentation of infant hippocampus from Magnetic Resonance (MR) images is one of the key steps for the investigation of early brain development and neurological disorders. Since the manual delineation...
-
Chapter and Conference Paper
Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework
In this paper, we present the results of evaluating our fully automatic intervertebral disc (IVD) localization and segmentation method using the training data and the test data provided by the localization and...
-
Chapter and Conference Paper
Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis
Segmentation of isointense infant brain (at ~ 6-month-old) MR images is challenging due to the ongoing maturation and myelination process in the first year of life. In particular, signal contrast between white...
-
Chapter and Conference Paper
Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-High Field MRI
Ultra-high field MR imaging (e.g., 7T) provides unprecedented spatial resolution and superior signal-to-noise ratio, compared to the routine MR imaging (e.g., 1.5T and 3T). It allows precise depiction of small...
-
Chapter and Conference Paper
Prediction of Infant MRI Appearance and Anatomical Structure Evolution Using Sparse Patch-Based Metamorphosis Learning Framework
Magnetic resonance imaging (MRI) of pediatric brain provides invaluable information for early normal and abnormal brain development. Longitudinal neuroimaging has spanned various research works on examining in...
-
Chapter and Conference Paper
Fast Regions-of-Interest Detection in Whole Slide Histopathology Images
In this paper, we present a novel superpixel based Region of Interest (ROI) search and segmentation algorithm. The proposed superpixel generation method differs from pioneer works due to its combination of bou...
-
Chapter and Conference Paper
A Novel Cell Orientation Congruence Descriptor for Superpixel Based Epithelium Segmentation in Endometrial Histology Images
Recurrent miscarriage can be caused by an abnormally high number of Uterine Natural Killer (UNK) cells in human female uterus lining. Recently a diagnosis protocol has been developed based on the ratio of UNK ...
-
Chapter and Conference Paper
Block-Based Statistics for Robust Non-parametric Morphometry
Automated algorithms designed for comparison of medical images are generally dependent on a sufficiently large dataset and highly accurate registration as they implicitly assume that the comparison is being ma...
-
Chapter and Conference Paper
Laplacian Shape Editing with Local Patch Based Force Field for Interactive Segmentation
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...
-
Chapter and Conference Paper
Learning Multi-scale Representations for Material Classification
The recent progress in sparse coding and deep learning has made unsupervised feature learning methods a strong competitor to hand-crafted descriptors. In computer vision, success stories of learned features ha...
-
Chapter and Conference Paper
Virtual Humans: Evolving with Common Sense
While the quality and robustness of animation techniques for virtual human have improved greatly over the past couple of decades, techniques for improving their intelligence have not kept pace. Ideally, agents...
-
Chapter and Conference Paper
3D Modeling for Deformable Objects
This paper presents an efficient BSpline surface reconstruction technique for modelling deformable objects. The differences of our methods from previous BSpline fitting approaches are: 1) the reconstructed BSp...
-
Chapter and Conference Paper
Certain Object Segmentation Based on AdaBoost Learning and Nodes Aggregation Iterative Graph-Cuts
In this paper, a fast automatic segmentation algorithm based on AdaBoost learning and iterative Graph-Cuts are shown. AdaBoost learning method is introduced for automatically finding the approximate location o...
-
Chapter and Conference Paper
Image Cues Fusion for Object Tracking Based on Particle Filter
Particle filter is a powerful algorithm to deal with non-linear and non-Gaussian tracking problems. However the algorithm relying only upon one image cue often fails in challenging scenarios. To overcome this,...
-
Chapter and Conference Paper
Multiple Facial Feature Tracking Using Multi-cue Based Prediction Model
It is challenging to track multiple facial features simultaneously in video while rich facial expressions are presented in a human face. To accurately predict the positions of multiple facial features’ contour...
-
Chapter and Conference Paper
The Lie Model for Euclidean Geometry
In this paper we investigate the Lie model of Lie sphere geometry using Clifford algebra. We employ it to Euclidean geometric problems involving oriented contact to simplify algebraic description and computation.
