The cell nucleus is mechanosensitive, making nuclear mechanics important for understanding how cells interact with their environment [1]. While methods such as AFM and micropipette aspiration measure bulk nuclear stiffness, subnuclear stiffness resolution remains largely unknown [1]. Here, we introduce an image-based full-field elastography method that registers image pairs to generate displacement fields, which are then input into an iterative inverse solver to produce full-field relative stiffness maps. The method was validated using finite element forward models built from nuclear images and subjected to equiaxial strain to generate paired undeformed–deformed images. For experimental data, microscopy images at defined timepoints captured H2B-eGFP-tagged nuclei from mouse embryonic skin fibroblasts (MEFs) subjected to 0–20% equiaxial strain for 30 minutes followed by a 30-minute recovery [2]. MEF nuclei subjected to 10% and 20% equiaxial strain showed broader stiffness distributions, with decreased 5th-percentile and increased 95th-percentile stiffness (Fig. 1A,B), indicating spatial heterogeneity. Stiffness was associated separately with chromatin intensity and nuclear border curvature, with higher intensity and higher curvature regions showing increased lower-bound stiffness (Fig. 1C,D), indicating a structural basis for stiffness patterns. Together, these findings show that nuclear stiffness has complex spatial variation that can be masked when using bulk stiffness measurements, highlighting the value of this elastography method for studying nuclear mechanical response at subnuclear resolution. Future work will integrate gene localization data and subnuclear relative stiffness maps to better understand relationships between gene activity and the local nuclear mechanical environment.