Patent ID: 11823375

Abstract:
Provided are a machine learning device and a method capable of performing machine learning of labeling for accurately attaching a plurality of labels to volume data at once by using learning data with mixed inconsistent labeling. A neural network (14) receives an input of multi-slice images of learning data Di (i=1, 2, . . . n) of which a class to be labeled is n types, and creates a prediction mask of n anatomical structures i by a convolutional neural network (CNN) or the like (S1). A machine learning unit (13) calculates a prediction accuracy acc(i) of the class corresponding to the learning data Di for each learning data Di (S2). The machine learning unit (13) calculates a weighted average M of an error di between the prediction accuracy acc(i) and a ground truth mask Gi. The machine learning unit (13) calculates a learning loss by a loss function Loss (S4). The machine learning unit (13) changes each coupling load of the neural network (14) from an output layer side to an input layer side according to a value of the learning loss calculated by the loss function Loss (S5).