SE-Mask-RCNN：多参数MRI前列腺癌分割方法

黄毅鹏,胡冀苏,钱旭升,周志勇,赵文露,马麒,沈钧康,戴亚康

SE-Mask-RCNN: segmentation method for prostate cancer on multi-parametric MRI

Yi-peng HUANG,Ji-su HU,Xu-sheng QIAN,Zhi-yong ZHOU,Wen-lu ZHAO,Qi MA,Jun-kang SHEN,Ya-kang DAI

表 1 前列腺癌病灶分割不同网络模型结果的定量比较

Tab.1 Quantitative comparison of different network model results of prostate cancer lesion segmentation

网络模型 MRI类型 DSC 敏感度 特异度 PPV U-net ADC 0.539 0.639 0.970 0.324 V-net ADC 0.525 0.707 0.945 0.472 Resnet50-U-net ADC 0.525 0.720 0.956 0.462 Mask-RCNN ADC 0.592 0.582 0.979 0.680 U-net T2W 0.370 0.651 0.886 0.283 V-net T2W 0.343 0.580 0.896 0.282 Resnet50-U-net T2W 0.349 0.624 0.902 0.276 Mask-RCNN T2W 0.403 0.395 0.962 0.473 U-net ADC+T2W 0.562 0.765 0.955 0.480 V-net ADC+T2W 0.553 0.763 0.949 0.476 Resnet50-U-net ADC+T2W 0.561 0.683 0.972 0.532 Mask-RCNN ADC+T2W 0.612 0.653 0.968 0.650