In ImageJ, there are at least two additional filament enhancement methods. Sato et al. 'Tubeness’ and Law & Chung Optimally Oriented Flux. If you take a look at their principle, Tubeness is similar to Frangi in the sense that it uses multi-scale eigenvalues of the Hessian matrix and use heuristic parameters to detect more specific kinds of structures, filament-like structures, and that is the reason it fails in enhancing branches/connections between those filaments. On the other hand, OOF is a more general curvilinear structure detector.
The details specific to the ImageJ implementations are here:
Unfortunately, I have tried using OOF myself and the implementation doesn’t appear to be working (see thread I posted). I would be glad if you try using on your computer (and saying our OS) to check if the problem also happens with you.
I am not sure of an ImageJ implementation but I know of a filament enhancement method that uses the concept of Phase congruency tensor (PCT) to fix the issue of not detecting branches/coneections in filament-like structures. This is the work proposed by Obara and collaborators (2012), another work of the same method is here. Their implementation is in Matlab.
- Is your image 2D or 3D?
- Have you considered using filament tracing methods that do not necessarily use a filament enhancement method prior to detection? For example, the first choice of the Simple Neurite Tracer or Anamorf (2D images only). Also ridge detection could be useful depending on what you are looking for in your images.
- If you wish to continue using Frangi or Sato enhancement methods, maybe it would be a good idea to try to use grayscale morphology closing (link1 link2) operator, to see if you could close these branch points.
I hope this helped.