摘要

本文是关于分割在医学场景中的应用。一般的分割任务有确定的真值，但是对于一些医学任务，我们往往需要结合多个专家的诊断结果作为真值，传统的方法是平均各个专家的诊断结果作为真值，但是专家往往由于经验和水平的高低，诊断也有所差别，传统方法显然没能很好地利用这些信息，因此本文提出MRNet。

1. Introduction

2. Related Work

3. Methodology

3.1. Motivation

从图中可以看出，每个专家用自己的模型训练出来的效果都是最好的，在综合投票中，专家一的得分最高，从数据库中的数据也确实如此，专家一是经验最丰富的。

3.2. Overall Framework

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