1. A method for segmenting a digital image of biological cells, comprising the steps: determining a maximum gradient for each pixel of the digital image as a maximum difference between a pixel value of the pixel and the respective pixel values of all or selected neighboring pixels, determining a segmentation threshold value using frequencies of the maximum gradients, comprising the steps of a) assigning a gradient frequency to all maximum gradients as a number of pixels having the respective maximum gradient, b) determining a value of an environment variable as a number of pixels for which the most frequent maximum gradient was determined, c) iteratively comparing the value of the environment variable and a predefined estimate for a number of pixels depicting the environment of a biological cell, and adding the number of pixels having the next most frequent maximum gradient to the value of the environment variable until the value of the environment variable exceeds or reaches the estimated value, and d) determining the segmentation threshold value from a number of repetitions of step c), classifying the pixels into an object class and an environment class using the segmentation threshold value, those pixels whose maximum gradient is equal to or greater than the segmentation threshold value being allocated to the object class, and the other pixels being allocated to the environment class, and forming a segmentation zone of the digital image using a class merging method.