Abstract: The present invention provides a task interaction network which can jointly perform, based on multi parametric-magnetic resonance imaging scan images, a segmentation task to locate prostate cancer areas and a classification task to access aggressiveness of lesions. The task interaction network comprises a backbone network, an auxiliary segmentation branch, a classification branch having a lesion awareness module, and a main segmentation branch having a category allocation module. The auxiliary segmentation branch is utilized to predict an initial lesion mask as location guidance information for the classification branch to perform the classification task. The lesion awareness module is configured to refine the initial lesion mask to make it more accurate. Moreover, weights used in classification branch can serve as the category prototypes for generating category guidance features via the category allocation module to assist the main segmentation branch to perform the segmentation task.

Abstract: The present invention provides a task interaction network which can jointly perform, based on multi parametric-magnetic resonance imaging scan images, a segmentation task to locate prostate cancer areas and a classification task to access aggressiveness of lesions. The task interaction network comprises a backbone network, an auxiliary segmentation branch, a classification branch having a lesion awareness module, and a main segmentation branch having a category allocation module. The auxiliary segmentation branch is utilized to predict an initial lesion mask as location guidance information for the classification branch to perform the classification task. The lesion awareness module is configured to refine the initial lesion mask to make it more accurate. Moreover, weights used in classification branch can serve as the category prototypes for generating category guidance features via the category allocation module to assist the main segmentation branch to perform the segmentation task.