Hyperparameter optimization for image analysis: application to prostate tissue images and live cell data of virus-infected cells - Ritter, Christian; Wollmann, Thomas; Gunkel, Manuel; Braun, Delia; Lee, Ji Young; Erfle, Holger; Rippe, Karsten; Bartenschlager, Ralf; Rohr, Karl (International journal of computer assisted radiology and surgery, 2019)
Automated analysis of microscopy image data typically requires complex pipelines that involve multiple methods for different image analysis tasks. To achieve best results of the analysis pipelines, method-dependent hyperparameters need to be optimized. However, complex pipelines often suffer from the fact that calculation of the gradient of the loss function is analytically or computationally infeasible. Therefore, first- or higher-order optimization methods cannot be applied.