Hyperspectral bioimaging techniques such as infrared (IR) microscopy and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) produce high-dimensional, spatially resolved datasets that require sophisticated analysis to reveal chemically and anatomically meaningful structures. Existing software solutions are typically modality-specific and cover only parts of the analytical workflow, forcing researchers to transfer data across multiple tools and manually reconcile results. We present MIA (Multiscale Image Analysis), a modality-agnostic visual analysis environment that integrates the full exploratory workflow -- from spectral preprocessing and dimensionality reduction to interactive segmentation and spectral similarity analysis -- within a single, tightly coupled interface. MIA supports hierarchical and landmark-based embeddings to handle datasets of varying scale and complexity, interactive and automatic segmentation with a shared state across all linked views, and multimodal analysis of co-registered datasets from different instruments. We demonstrate the effectiveness of MIA through three use cases drawn from real analytical chemistry workflows: (1) the recovery of biologically meaningful tissue compartments through derivative preprocessing and hierarchical embedding, (2) pigment identification via spectral similarity search with spatial overview, and (3) multimodal tissue characterization combining molecular IR and elemental LA-ICP-MS data. Qualitative feedback from domain expert collaborators confirms that MIA reduces the need for tool-switching and supports analytical insights that are difficult to obtain with existing software.

翻译：高光谱生物成像技术（如红外显微成像与激光剥蚀-电感耦合等离子体质谱）所生成的高维、空间解析数据集，需要通过精密分析来揭示具有化学与解剖学意义的组织结构。现有软件解决方案通常仅针对特定模态，且仅覆盖分析工作流的部分环节，迫使研究人员在多个工具之间传输数据并手动整合结果。我们提出MIA（多尺度图像分析系统）——一个模态无关的可视分析环境，将光谱预处理、降维、交互式分割及光谱相似性分析等完整探索性工作流集成于单一紧密耦合的界面中。该系统支持基于层次化与地标式嵌入的方法以处理不同尺度与复杂度的数据集，通过跨关联视图的共享状态实现交互式与自动分割，并支持来自不同仪器的联合配准数据的多模态分析。我们通过三个源自实际分析化学工作流的案例验证了MIA的有效性：（1）基于导数预处理与层次化嵌入恢复具有生物学意义的组织区域；（2）结合空间概览的光谱相似性搜索进行色素鉴定；（3）融合分子红外与元素LA-ICP-MS数据的多模态组织表征。领域专家合作者的定性反馈表明，MIA降低了工具切换需求，并支持了现有软件难以实现的分析洞察。