Finite topology as applied to image analysis
Computer Vision, Graphics, and Image Processing
A critical view of pyramid segmentation algorithms
Pattern Recognition Letters
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
International Journal of Computer Vision
A causal extraction scheme in top-down pyramids for large images segmentation
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Mitosis extraction in breast-cancer histopathological whole slide images
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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Recent microscopic imaging systems such as whole slide scanners provide very large (up to 18GB) high resolution images. Such amounts of memory raise major issues that prevent usual image representation models from being used. Moreover, using such high resolution images, global image features, such as tissues, do not clearly appear at full resolution. Such images contain thus different hierarchical information at different resolutions. This paper presents the model of tiled top-down pyramids which provides a framework to handle such images. This model encodes a hierarchy of partitions of large images defined at different resolutions. We also propose a generic construction scheme of such pyramids whose validity is evaluated on an histological image application.