The evaluation of human epidermal growth factor receptor 2 (HER2) expression
is essential to formulate a precise treatment for breast cancer. The routine
evaluation of HER2 is conducted with immunohistochemical techniques (IHC),
which is very expensive. Therefore, for the first time, we propose a breast
cancer immunohistochemical (BCI) benchmark attempting to synthesize IHC data
directly with the paired hematoxylin and eosin (HE) stained images. The dataset
contains 4870 registered image pairs, covering a variety of HER2 expression
levels. Based on BCI, as a minor contribution, we further build a pyramid
pix2pix image generation method, which achieves better HE to IHC translation
results than the other current popular algorithms. Extensive experiments
demonstrate that BCI poses new challenges to the existing image translation
research. Besides, BCI also opens the door for future pathology studies in HER2
expression evaluation based on the synthesized IHC images. BCI dataset can be
downloaded from this https URL

提出了一种乳腺癌免疫组化标准，能够通过 HE 染色图像的合成直接综合 IHC 数据，可用于 HER2 表达评估的病理研究。