Ice shelves buttress the discharge of Antarctica’s outlet glaciers, mitigating their contribution to sea-level rise. Yet progressive damage through fracturing remains largely absent from projections, partly because long-term observations of ice-shelf fractures remain limited despite their critical influence on ice-shelf stability. Here, we introduce BASIS (BAsal and Surface Ice-shelf fracture extraction System), a deep-learning model for mapping surface crevasses and basal-fracture across Antarctic ice shelves. Unlike existing approaches based on classical edge detectors or models trained on edge-based datasets, BASIS is designed to delineate the full extent of fracture features, including diffuse basal-fracture signatures and highly damaged, chaotic regions. We train, validate, and test BASIS, based on DeepLabv3, using a unique manually labeled fracture dataset spanning 14 Antarctic ice shelves and the full Landsat observation era. Model performance approaches inter-annotator agreement, while maintaining the distinction between basal and surface fractures. We quantify biases associated with sensor transitions and observation availability and develop a framework for producing consistent multi-sensor fracture records. Annual mosaics reveal the spatiotemporal evolution of ice-shelf damage from the 1980s onward and show that basal-fracture signatures dominate the mapped damage patterns across the ice shelves examined here. At Pine Island Glacier Ice Shelf, BASIS resolves successive stages of shear-margin damage together with a progressive increase in basal-fracture. At Mertz and Borchgrevink ice shelves, it reveals extensive networks of basal-fracture signatures that are poorly represented in existing continent-wide products based on Sentinel-1 SAR imagery. Finally, BASIS demonstrates promising cross-sensor transferability to Sentinel-2 and ASTER optical imagery and, despite having been trained exclusively on Landsat data, also recovers coherent fracture patterns from SAR imagery. These results provide a foundation for large-scale, multi-sensor monitoring of Antarctic ice-shelf damage across unprecedented spatial and temporal scales.