Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm
This work addresses image registration for histological analysis, but it is incremental as it builds on existing methods for a specific challenge.
The authors tackled the problem of nonrigid histological image registration by proposing an adaptive multistep algorithm, achieving 99.792% robustness and 0.38% average median rTRE accuracy.
In this paper, we present a short description of the method proposed to ANHIR challenge organized jointly with the IEEE ISBI 2019 conference. We propose a method consisting of preprocessing, initial alignment, nonrigid registration algorithms and a method to automatically choose the best result. The method turned out to be robust (99.792% robustness) and accurate (0.38% average median rTRE). The main drawback of the proposed method is relatively high computation time. However, this aspect can be easily improved by cleaning the code and proposing a GPU implementation.