Histopathology Slide Indexing and Search: Are We There Yet?
This highlights a critical gap in clinical adoption of histopathology search tools, which is incremental as it assesses existing methods rather than introducing new ones.
The study evaluated three state-of-the-art histopathology slide search engines (Yottixel, SISH, RetCCL) on patients with solid tumors and found that they fail to produce consistently reliable results and struggle with capturing granular features, limiting diagnostic accuracy.
The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-of-the-art histopathology slide search engines, Yottixel, SISH, and RetCCL, on three patients with solid tumors. We provide a qualitative assessment of each model's performance in providing retrieval results that are reliable and useful to pathologists. We found that all three image search engines fail to produce consistently reliable results and have difficulties in capturing granular and subtle features of malignancy, limiting their diagnostic accuracy. Based on our findings, we also propose a minimal set of requirements to further advance the development of accurate and reliable histopathology image search engines for successful clinical adoption.