In ultrasonic structural health monitoring (SHM) and nondestructive evaluation (NDE), the scattered waves caused by damage sites and defects are the key to damage diagnosis. However, structural components and boundaries also interact with traveling waves, creating events that can bury damage scattered waves. The baseline subtraction method, which directly subtracts the waveform of a damage signal from that of a pristine baseline signal, is a common processing technique to separate these damage scattered waves. However, baseline subtraction is less effective when a component is measured in different environmental/loading conditions from when its baseline was recorded. For instance, baseline subtraction can be ineffective in aerospace structural parts because such parts expect significant and routine changes in ambient temperature, pressure, and humidity. To overcome the limitations of baseline subtraction, this paper proposes to develop an spex-shifted Radon transform (ASRT)-based damage scattered event extraction technique without baseline subtraction. Our proposed ASRT method converts the original time-space ( t − x ) domain signals to a time delay–curvature–apex offset ( τ − q − y ) domain, which targets specific geometries of scattered/reflected waves in the t − x domain and compresses them into a single point-like region in the new domain. In this domain, identifying and isolating targeted events becomes significantly easier. To benchmark the performance of this baseline-subtraction-free (BSF) method, ASRT is applied for signals acquired from (1) spectral finite element-based simulations to scan a water-immersed steel specimen (2) 3-D wave simulations in a bent aluminum plate, and (3) a full matrix capture for experimentally scanning a high-density polyethylene (HDPE) with multiple holes. The goal in each case is to target and separate events of interest from the original signals using the proposed algorithm. The results suggest the ASRT method is effective as a damage scattered wave extraction tool for ultrasonic SHM and NDE.