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Abstract Multimodal image registration plays a crucial role in biomedical research, enabling the integration of complementary information from different imaging techniques. We present a novel feature-based approach for multimodal image registration, alongside traditional intensity-based methods. Our method, inspired by SPP-net architecture, employs multi-level feature extraction for robust image alignment. Additionally, we perform t-SNE dimensionality reduction on the MALDI-MSI dataset to enhance feature discrimination and visualization. We evaluated both approaches using datasets from the ANHIR Grand Challenge and mass spectrometry imaging modalities (LA-ICP-MS and MALDI-MSI). The proposed feature-based method achieved comparable accuracy to optimized intensity-based approaches, with Dice Coefficients of 0.95 for ANHIR samples (e.g., COAD_05) and 0.97 for mass spectrometry data, while requiring approximately 50% less computational time. Quantitative evaluation through Mutual Information metrics and Hausdorff Distance demonstrated high registration accuracy across different tissue types and imaging modalities. These results establish our feature-based approach as an efficient alternative to traditional intensity-based methods for multimodal image registration in biomedical applications. 

Quantitative imaging of nanomaterials in sub-organ regions using gelatin-based standards. 

Faradays legendary Molecules of Gold have stimulated intense interest (over 165 years) but have only recently begun to yield their secrets to modern methods of chemical analysis. Here(in), we demonstrate how striking charging patterns emerge directly from native electrospray of large, gold-rich molecules that were generated by reduction of various (8) small gold(I)thiolate complexes [-RS-Au(I)-SR-], followed by extensive thermochemical processing to enrich the most robust forms. In each case (R), electrospray ionization of a picomolar solution yields a characteristic series of abundant, highly resolved peaks at related (m/z)-ratios, that can be used to deduce charges {z e+} and hence a distinct molecular mass, {MR}. A plot of {MR} versus thiolate-mass {mL} yields a straight line with slope 60.0 (the ligand count) and an intercept of 28,364-Da, the mass of 144 Au-atoms. i.e., a unique molecular composition {197Au144(SR)60}. This formula agrees with the unique chiral-icosahedral structure-model, c@12@42@60@(30,60), the Pd145(CO)60-structure, that features a massively-compact globular Au114-core (~1.6-nm) and an intrinsically chiral (I) outer shell (~2.0-nm) with 12 distinct ligand types of 5-fold equivalence], denoted by Martin et al. as virus-like on the basis of its resemblance of icosahedral-virus capsids.