This work describes an array of 1024 Ion-Sensitive Field-Effect Transistors (ISFETs) using sensor learning techniques to perform multi-ion imaging for concurrent detection of potassium, sodium, calcium and hydrogen. Analyte specific ionophore membranes are deposited on the surface of the ISFET array chip, yielding pixels with quasi-Nernstian sensitivity to K+, Na+ or Ca2+. Uncoated pixels display pH sensitivity from the standard Si3N4 passivation layer. The platform is then trained by inducing a change in single ion concentration and measuring the responses of all pixels. Sensor learning relies on k-means clustering and DBSCAN to yield membrane mapping and sensitivity of each pixel to target electrolytes. We demonstrate multi-ion imaging with an average error of 3.7 % (K+), 4.6 % (Na+), and 1.8 % (pH) for each ion respectively, while Ca2+ incurs a larger error 24.2 % and hence is included to demonstrate versatility. We validate the platform with a brain dialysate fluid sample and demonstrate reading by comparing with a gold-standard spectrometry technique.