Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Deviations from Normalcy for Brain Tumor Segmentation
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Pattern Recognition Letters
Efficient adaptive density estimation per image pixel for the task of background subtraction
Pattern Recognition Letters
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
SBRN '06 Proceedings of the Ninth Brazilian Symposium on Neural Networks
Approaches for automated detection and classification of masses in mammograms
Pattern Recognition
Description of interest regions with local binary patterns
Pattern Recognition
Automated detection of drusen in the macula
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Expert Systems with Applications: An International Journal
Histopathological Diagnostic Support Technology Using Higher-Order Local Autocorrelation Features
BLISS '09 Proceedings of the 2009 Symposium on Bio-inspired Learning and Intelligent Systems for Security
Detection of microaneurysms using multi-scale correlation coefficients
Pattern Recognition
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Local descriptor based on texture of projections
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Advanced Radon transform using generalized interpolated Fourier method for straight line detection
Computer Vision and Image Understanding
Background learning for robust face recognition with PCA in the presence of clutter
IEEE Transactions on Image Processing
Motion pattern-based image features for glaucoma detection from retinal images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
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Detection of abnormalities from medical images is of key interest in developing computer-aided diagnostic tools. In this paper, we observe the key challenges for representation and feature extraction schemes to be met for detection of abnormalities by learning normal cases. We introduce an image representation, motivated by the effect of motion on perception of structures. This representation is based on a set of patterns called generalized moment patterns (GMP) generated via induced motion over regions of interest, for learning normal. The proposed GMP has been utilized to develop a scheme for addressing two well-known problems: lesion classification in mammograms and detection of macular edema in color fundus images. The strengths of this scheme are that it does not require any lesion-level segmentation and relies largely on normal images for training which is attractive for developing screening tools. The proposed scheme has been assessed on two public domain datasets, namely, MIAS and MESSIDOR. A comparison against the performance of state of the art methods indicates the proposed scheme to be superior.