Immunohistochemistry (IHC) biomarkers are essential tools for reliable cancer
diagnosis and subtyping. It requires cross-staining comparison among Whole
Slide Images (WSIs) of IHCs and hematoxylin and eosin (H&E) slides. Currently,
pathologists examine the visually co-localized areas across IHC and H&E glass
slides for a final diagnosis, which is a tedious and challenging task.
Moreover, visually inspecting different IHC slides back and forth to analyze
local co-expressions is inherently subjective and prone to error, even when
carried out by experienced pathologists. Relying on digital pathology, we
propose Composite Biomarker Image (CBI) in this work. CBI is a single image
that can be composed using different filtered IHC biomarker images for better
visualization. We present a CBI image produced in two steps by the proposed
solution for better visualization and hence more efficient clinical workflow.
In the first step, IHC biomarker images are aligned with the H&E images using
one coordinate system and orientation. In the second step, the positive or
negative IHC regions from each biomarker image (based on the pathologists
recommendation) are filtered and combined into one image using a fuzzy
inference system. For evaluation, the resulting CBI images, from the proposed
system, were evaluated qualitatively by the expert pathologists. The CBI
concept helps the pathologists to identify the suspected target tissues more
easily, which could be further assessed by examining the actual WSIs at the
same suspected regions.

使用数字病理学，本文提出了一种名为 CBI 的复合生物标记物图像，它使用不同过滤的免疫组化生物标记物图像进行组合以实现更好的可视化，并且更有效的临床工作流程。