Telemicroscopy system applied to digital microscopy with a low-cost automated microscope

Market-available automated microscopy systems are often unaffordable for research institutions, particularly in economically disadvantaged countries, limiting their access to advanced technologies. This work addresses this challenge by developing a cost-effective virtual microscopy and telemicroscopy system, aimed at creating a remote-controlled microscopy setup for analyzing digital samples with performance comparable to high-end equipment but at a reduced cost. The system includes a web platform for telemicroscopy, enabling remote control of the robotic stage and real-time viewing of the microscope camera. Additionally, a decision support system has been implemented, integrating AI-based models for identifying and classifying objects of interest in three histopathology use cases for breast cancer analysis: i) identification of tumor cells in H&E samples; ii) grading of Her2 samples; and iii) evaluation of Ki67 samples. These models enhance diagnostic capabilities, increasing productivity for experts and reducing manual workload. Sample virtualization and automatic processing simplify tasks for professionals, allowing remote participation in concurrent work sessions and streamlining processes for digital samples.