With the progression of diseases, modified cell–matrix interactions have major effects not only upon key cellular functions but also upon the structure of extracellular matrix and vasculature, which are two of the most prevalent fiber‐like structures in biological tissues. Unfortunately, quantitative approaches to assessing these structural changes are lacking. Herein, a multiparametric imaging system is established to resolve subtle organizational changes of collagen fibers and vasculature in disease progression. The pixel‐wise, automated waviness (paWav) is developed as a novel biomarker, and a multimodal analysis system combining paWav with orientation and alignment assessments is constructed. Aggregation‐induced emission luminogens (AIEgens) with second near‐infrared excitation or emission are developed for in vivo deep‐penetration vasculature imaging. The organization remodeling of cortical blood vessels in stroke in marmosets is quantitatively characterized using biologically excretable AIE dots that highlight the clinical translation potential, and a distance dependence law in vessel morphological remodeling is identified. Finally, the multiparametric analysis relying completely on collagen fiber signatures successfully differentiates cancerous from normal pancreatic tissues using a predictive classification approach. Collectively, the combined use of these structural changes in fibrillar tissue components may enable a better understanding of cell–matrix interactions in pathogenesis and identification of new potential treatment targets.

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