Deep learning is widely used for lesion segmentation in medical images due to its breakthrough performance.Loss functions are critical in a deep learning pipeline,and they play important roles in segmenting performanc...Deep learning is widely used for lesion segmentation in medical images due to its breakthrough performance.Loss functions are critical in a deep learning pipeline,and they play important roles in segmenting performance.Dice loss is the most commonly used loss function in medical image segmentation,but it also has some disadvantages.In this paper,we discuss the advantages and disadvantages of the Dice loss function,and group the extensions of the Dice loss according to its improved purpose.The performances of some extensions are compared according to core references.Because different loss functions have different performances in different tasks,automatic loss function selection will be the potential direction in the future.展开更多
文摘Deep learning is widely used for lesion segmentation in medical images due to its breakthrough performance.Loss functions are critical in a deep learning pipeline,and they play important roles in segmenting performance.Dice loss is the most commonly used loss function in medical image segmentation,but it also has some disadvantages.In this paper,we discuss the advantages and disadvantages of the Dice loss function,and group the extensions of the Dice loss according to its improved purpose.The performances of some extensions are compared according to core references.Because different loss functions have different performances in different tasks,automatic loss function selection will be the potential direction in the future.
