Introduction/Background: Digital pathology is growing fast, yet interoperability and viewer extensibility still limit whole slide imaging (WSI) and multiplex microscopy. Open-source, standards-based viewers can lower integration cost and improve reproducibility. We present two NCI Imaging Data Commons (IDC) projects: DICOM Microscopy Viewer (DMV, a toolkit) and SLIM (a full web app) for DICOM WSI/microscopy.

Methods/Design: We outline browser workflows to load/render DICOM WSI, overlays, and derived objects (annotations, segmentations, parametric maps). Recent work targets key user needs: multiplex channel blending, better annotation/segmentation interactions, derived-image controls, centralized error handling, and smoother packaging/deployment.

Results: New capabilities include improved multi-channel coloring/blending with performance gains (parallel pixel processing); clearer annotation/segmentation UX (selection, hover labels/tooltips, fractional visualization, metadata-driven colors); safer dynamic-import deployment and dependency alignment; and end-to-end error capture with user-facing diagnostics across DICOMweb, parsing, and rendering. Thus, reducing friction and speeding troubleshooting.

Conclusion/Discussion: DMV and SLIM have moved beyond connectathon prototypes but retain tech debt (architecture, tests, infra/DevOps) and need more contributors. We share IDC production lessons from SLIM, highlight near-term fixes, and discuss roadmap directions to improve maturity and sustainability.

Acknowledgments: The discussed open-source tools are maintained by the IDC team, are available at https://github.com/ImagingDataCommons, and have been funded in whole or in part with Federal funds from the NCI, NIH, under task order no. HHSN26110071 under contract no. HHSN261201500003I.

Learning Objectives:

1. Explain how DICOM enables interoperable WSI/microscopy viewing using DICOM Microscopy Viewer and Slim.
2. Identify recent viewer features that improve user experience, performance, and reliability vs. future roadmaps.
3. Apply practical patterns for deploying, integrating, and contributing to open-source digital pathology viewers.