A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Discriminative cue integration for medical image annotation
Pattern Recognition Letters
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
SIFT and shape context for feature-based nonlinear registration of thoracic CT images
CVAMIA'06 Proceedings of the Second ECCV international conference on Computer Vision Approaches to Medical Image Analysis
A refined SVM applied in medical image annotation
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Automated cephalometric landmark localization using sparse shape and appearance models
MLMI'11 Proceedings of the Second international conference on Machine learning in medical imaging
MICCAI'10 Proceedings of the Second international conference on Virtual Colonoscopy and Abdominal Imaging: computational challenges and clinical opportunities
Generating time lines with virtual words for time-varying data visualization
Proceedings of the 5th International Symposium on Visual Information Communication and Interaction
Evaluation of medical image registration by using 3d SIFT and phase-only correlation
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
Computer Vision and Image Understanding
Visualization and analysis of 3D time-varying simulations with time lines
Journal of Visual Languages and Computing
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We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.