促進數位病理學發展：Mainecoon 台灣開源病理影像顯示器介紹及開發經驗
Due to the rapid development of digital pathology, we face challenges such as data format differences from various pathology scanning devices, which create certain difficulties for practical applications in medical settings. To address this, we have developed an innovative open-source digital pathology image display platform called Mainecoon. This platform integrates the DICOM standard and supports Whole Slide Images (WSI) from different scanner brands. By optimizing front-end transmission performance, it addresses the issue of prolonged transmission times for large annotations. Additionally, we have developed an integrated AI model framework and conducted integration test cases with physical hospitals to resolve data interoperability issues in the field of digital pathology. In this session, we will introduce a digital microscope with interoperability capabilities!
由於數位病理學的快速發展，我們面對來自不同病理掃描設備的資料格式差異等挑戰，對於實際醫療場域的應用造成了一定的困難。為此，我們開發了一個創新的開源數位病理影像顯示平台-緬因貓（Mainecoon），該平台整合了DICOM標準，支持不同掃描廠牌的全玻片數位病理影像（Whole Slide Image, WSI），透過優化前端傳輸效能以解決大型標記傳輸時間過長的問題，開發整合AI模型框架，並結合實體醫院進行整合測試案例，以解決數位病理領域的資料互通性問題。