Signal Perception in Two-Dimensional Mapping Techniques: Just Noticeable Difference as a Visual Limit of Detection

Abstract

The limit of detection (LOD) is a ubiquitous figure of merit for characterizing the performance of instrumental methods in analytical chemistry, with the well-known formula "three times the standard deviation of the blank" serving as a common heuristic for assessing signal detection. However, in two-dimensional (2D) data settings from elemental imaging and mapping techniques, signals below the LOD often remain visually discernible. Inspired by the theory of psychophysics, we propose the Just-Noticeable Difference (JND) as a novel figure of merit for chemical data analysis in 2D contexts. The JND refers to the smallest perceptible difference between two stimuli by the human senses. By utilizing the JND as a guiding principle in targeting low-contrast signals, we offer an alternative approach to understanding detection limits in 2D data sets, with enhanced sensitivity for a large variety of sizes of spatially resolved signal and noise levels. The potential of this approach, which is presented in two different mapping techniques, LA-ICP-MS and LIBS, is compared to the standard LOD metric, which hints at the possibility for more accurate assessments of elemental concentrations and better utilization of contrast variations and spatial information inherent in mapping techniques.