Automated Scoring System of HER2 in Pathological Images under the
Microscope
- URL: http://arxiv.org/abs/2110.12900v1
- Date: Thu, 21 Oct 2021 01:38:35 GMT
- Title: Automated Scoring System of HER2 in Pathological Images under the
Microscope
- Authors: Zichen Zhang, Lang Wang, and Shuhao Wang
- Abstract summary: We propose a HER2 automated scoring system that strictly follows the HER2 scoring guidelines.
The proposed system will be embedded in our Thorough Eye platform for deployment in hospitals.
- Score: 3.689994643251581
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Breast cancer is the most common cancer among women worldwide. The human
epidermal growth factor receptor 2(HER2) with immunohistochemical(IHC) is
widely used for pathological evaluation to provide the appropriate therapy for
patients with breast cancer. However, the deficiency of pathologists is
extremely significant in the current society, and visual diagnosis of the HER2
overexpression is subjective and susceptible to inter-observer variation.
Recently, with the rapid development of artificial intelligence(AI) in disease
diagnosis, several automated HER2 scoring methods using traditional computer
vision or machine learning methods indicate the improvement of the HER2
diagnostic accuracy, but the unreasonable interpretation in pathology, as well
as the expensive and ethical issues for annotation, make these methods still
have a long way to deploy in hospitals to ease pathologists' burden in real. In
this paper, we propose a HER2 automated scoring system that strictly follows
the HER2 scoring guidelines simulating the real workflow of HER2 scores
diagnosis by pathologists. Unlike the previous work, our method takes the
positive control of HER2 into account to make sure the assay performance for
each slide, eliminating work for repeated comparison and checking for the
current field of view(FOV) and positive control FOV, especially for the
borderline cases. Besides, for each selected FOV under the microscope, our
system provides real-time HER2 scores analysis and visualizations of the
membrane staining intensity and completeness corresponding with the cell
classification. Our rigorous workflow along with the flexible interactive
adjustion in demand substantially assists pathologists to finish the HER2
diagnosis faster and improves the robustness and accuracy. The proposed system
will be embedded in our Thorough Eye platform for deployment in hospitals.
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