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(AAAI 2017) Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images

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Keyword [MRI]

Yu L, Yang X, Chen H, et al. Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images[C]//AAAI. 2017: 66-72


1. Overview

目前prostate MRI segmentation存在一些挑战

  • 不同MR扫描协议导致MRI存在差别
  • prostate MRI缺少清晰边界（prostate与周围组织很相似）
  • 不同病变或分辨率导致prostate形状大小变化很大
  • 3D MRI segmentation 耗时


因此，论文提出一种end-to-end train, volume-to-volume predict, 适用于limited training data的模型，并在MICCAI PROMISE12数据集上达到state-of-art结果。

1.1. 模型特点

  • 3D CNN
  • 存在down sampling和up sampling两个阶段
  • residual block和connection. block内部存在short connection, block之间存在long connection（恢复down sampling造成的空间信息丢失）. 能够增强局部信息和全局信息在整个网格中的传递，以及加快收敛，避免梯度问题
  • 加权(0.3, 0.6, 1) auxiliary cross-entropy loss. 加快收敛; Function as a strong regularization which is important for limited training data


1.2. Dig the Potential of limited data

  • Data augmentation. 但增加的信息量有限
  • 使用skip connection. 提升网络内信息的propagation

Multi-altas based method

  • Deformable method
  • Graph cut based mathod
  • Feature based machine learning method（Deep Learning）
  • 使用2D CNN aggregate 3D contextual feature. adjacent slices, orthogonal planes, multi-view planes. 但没有充分利用3D空间信息
  • 3D CNN. with residual block

1.4. 数据集

MICCAI PROMISE12

  • 训练集. 50 transversal T2-weighted MRI and segmentation gt
  • 测试集. 30 MRI, 未提供gt
    图像来自不同医院、设备、协议以及存在maximum variation in clinical setting (voxel size, dynamic range,position, field of view and anatomic appearance.).


2. Experiments

2.1. 数据预处理

  • resize MR volumes into 0.625x0.625x1.5 mm
  • 归一化
  • rotation (90°, 180°, 270°) , x-flip

2.2. 训练细节

  • batch size 8
  • lr 0.001 divided by 10 every 3000 iteration
  • weight decay 0.0005
  • SGD, 0.9 momentum
  • weighted loss (0.3, 0.6, 1)
  • 训练（4小时）. random crop 64x64x16 sub-volume
  • 测试（12 s/MRI, 320x320x60）. overlap sliding window (64x64x16), stride (50x50x12), average probability map

2.3. 评价指标

  • Dice coefficient (DSC). 链接


  • aRVD. absolute difference between volumes
  • ABD. average over shortest distance between the boundary points of volumes
  • 95HD (95% Hausdorff distance). 链接


2.4. Ablation



2.5. 实验结果