Amyloid diseases are characterized by the misfolding and deposition of proteins in the body in the form of insoluble amyloid fibrils. Alzheimer's disease and type 2 diabetes mellitus are two examples of amyloid diseases which are closely related both with respect to the atomic structures of the amyloid fibrils and the disease pathology. Alzheimer's disease is very difficult to diagnose, and much research is being performed to develop noninvasive diagnostic methods, such as imaging with small-molecule agents. The interactions between amyloid fibrils and imaging agents are challenging to examine experimentally due to the insoluble nature of amyloid fibrils. This study uses molecular dynamics simulations to investigate the interactions between 13 aromatic amyloid imaging agents, entailing 4 different organic scaffolds, and a model of an amyloid fibril. Clustering analysis combined with free energy calculations are used to categorize and rank the resulting complexes. Several binding modes are identified across the different ligand scaffolds, however a common favorable binding mode can be identified in which the agent is placed in surface grooves along the amyloid fibril axis. The existence of multiple binding modes for imaging agents is proposed to originate from subtle differences in amino acid composition of the surface grooves on an amyloid fibril, resulting in fine tuning of the binding affinities for a specific amyloid fibril.