Besides yielding numerical attributes, the metrics also produce images which can visually highlight differences. Our metrics are simple to compute and operate ...
In this paper, we propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial ...
Abstract. Often, images or datasets have to be compared, to facilitate choices of visualization and simulation parameters respectively. Common comparison ...
Besides yielding numerical attributes, the metrics also produce images which can visually highlight differences. Our metrics are simple to compute and operate ...
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Deciphering spatial domains from spatial multi-omics with SpatialGlue
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Jun 21, 2024 · We introduce SpatialGlue, a graph neural network model with a dual-attention mechanism that deciphers spatial domains by intra-omics integration.
Oct 17, 2022 · Spatial data augmentation and rational utilization of morphological image features can significantly improve DeepST performance. Additionally, ...
Jan 27, 2021 · I am assuming that your problem is similar to texture-pattern recognition. We can start with Local Binary Patterns (2002), or LBPs for short.
Nov 21, 2022 · Here we explore the application of spatial statistics to the cellular relationships within tissue microscopy data and discuss how spatial statistics offers ...
Oct 21, 2024 · We propose EnSDD (Ensemble-learning for Spatial Domain Detection), a method that ingeniously integrates eight state-of-the-art spatial domain detection methods.
Traditional image similarity metrics compare two images on a point-by-point basis. While such metrics can successfully account for perceptual effects, ...