We present an improved version of the ConFiG white matter numerical phantom generator to create realistic white matter microstructure. Building on ConFiG’s novel fibre growth algorithm, the enhancement incorporates a dynamic growth network and global optimisation of fibre positions. Resulting phantoms represent a significant improvement over those from the original ConFiG algorithm, with realistic morphology and an increase in packing density of up to 30%. These improved phantoms result in much more realistic simulated diffusion MRI signals, reducing RMSE to real data by ten times. This improvement demonstrates the potential of ConFiG as a computational model of white matter microstructure.