A system for medical image segmentation, comprising: an input module configured to provide a plurality of patches (2-i) of an N-dimensional medical image to be segmented; a computing device configured to implement a trained first neural network as a first controller network and a trained second neural network as a second controller network; wherein the first controller network is configured to sequentially receive input data (11-i) representing each of the plurality of patches (2-i) in a first patch sequence, and to sequentially generate and output data (13-i) indicative of a respective first patch segmentation mask candidate (14-i) for each of the plurality of patches (2-i); wherein the second controller network is configured to sequentially receive input data (21-i)representing each of the same plurality of patches (2-i) in a second patch sequence, and to sequentially generate and output data (23-i) indicative of a respective second patch segmentation mask candidate (24-i) for each of the plurality of patches (2-i); wherein the second patch sequence is different from the first patch sequence; a memory shared by the first and the second controller network (10, 20); wherein the first controller network is further configured to write data relating to a state of the first controller network to the memory; wherein the second controller network is configured to read at least part of the data written by the first controller network from the memory and to utilize the read data when generating the data (23-i) indicative of at least one of the second patch segmentation mask candidates (24-i); and wherein the computing device is further configured to generate, based on the data indicative of the first and second patch segmentation mask candidates (14-i, 24-i), a final image segmentation mask for segmenting the N-dimensional medical image. an input module configured to provide a plurality of patches (2-i) of an N-dimensional medical image to be segmented; a computing device configured to implement a trained first neural network as a first controller network and a trained second neural network as a second controller network; wherein the first controller network is configured to sequentially receive input data (11-i) representing each of the plurality of patches (2-i) in a first patch sequence, and to sequentially generate and output data (13-i) indicative of a respective first patch segmentation mask candidate (14-i) for each of the plurality of patches (2-i); wherein the second controller network is configured to sequentially receive input data (21-i)representing each of the same plurality of patches (2-i) in a second patch sequence, and to sequentially generate and output data (23-i) indicative of a respective second patch segmentation mask candidate (24-i) for each of the plurality of patches (2-i); wherein the second patch sequence is different from the first patch sequence; a memory shared by the first and the second controller network (10, 20); wherein the first controller network is further configured to write data relating to a state of the first controller network to the memory; wherein the second controller network is configured to read at least part of the data written by the first controller network from the memory and to utilize the read data when generating the data (23-i) indicative of at least one of the second patch segmentation mask candidates (24-i); and wherein the computing device is further configured to generate, based on the data indicative of the first and second patch segmentation mask candidates (14-i, 24-i), a final image segmentation mask for segmenting the N-dimensional medical image.