Chromogenic RNAscope dye and haematoxylin staining of cancer tissue
facilitates diagnosis of the cancer type and subsequent treatment, and fits
well into existing pathology workflows. However, manual quantification of the
RNAscope transcripts (dots), which signify gene expression, is prohibitively
time consuming. In addition, there is a lack of verified supporting methods for
quantification and analysis. This paper investigates the usefulness of gray
level texture features for automatically segmenting and classifying the
positions of RNAscope transcripts from breast cancer tissue. Feature analysis
showed that a small set of gray level features, including Gray Level Dependence
Matrix and Neighbouring Gray Tone Difference Matrix features, were well suited
for the task. The automated method performed similarly to expert annotators at
identifying the positions of RNAscope transcripts, with an F1-score of 0.571
compared to the expert inter-rater F1-score of 0.596. These results demonstrate
the potential of gray level texture features for automated quantification of
RNAscope in the pathology workflow.

此研究探讨了灰度纹理特征在乳腺癌组织中自动分割和分类 RNAscope 转录本位置的有用性，结果显示出灰度纹理特征的潜力，因其在自动化 RNAscope 定量方面与专家注释者表现相似（F1 得分：0.571 vs. 专家间 F1 得分：0.596），从而适用于病理学工作流程中的 RNAscope 定量分析。