
Arul Mozhi contributed to the OHIF/Viewers repository by delivering targeted improvements to medical imaging workflows over four months. He enhanced context menu reliability and accessibility for annotation tools, refined measurement label handling for arrow annotations, and fixed navigation logic in 2D MPR views to ensure accurate measurement switching and viewport selection. In addition, Arul implemented customizable slice ordering and robust handling of missing data for SEG/RTSTRUCT workflows, while updating test coverage to align with orientation and navigation changes. His work leveraged JavaScript, TypeScript, and React, demonstrating depth in DICOM, UI development, and testing for clinical imaging applications.

In July 2025, OHIF/Viewers focused on strengthening image navigation fidelity, resilience for SEG/RTSTRUCT workflows, and test coverage, delivering three key capabilities with measurable business value. The team improved data presentation accuracy in 2D MPR views, enhanced user experience during missing data scenarios, and stabilized orientation-related behavior across the viewer with updated tests.
In July 2025, OHIF/Viewers focused on strengthening image navigation fidelity, resilience for SEG/RTSTRUCT workflows, and test coverage, delivering three key capabilities with measurable business value. The team improved data presentation accuracy in 2D MPR views, enhanced user experience during missing data scenarios, and stabilized orientation-related behavior across the viewer with updated tests.
March 2025 – OHIF/Viewers: Targeted 2D MPR navigation bug fix and supporting utility; improved measurement switching correctness and viewport selection across multiple viewports. This work reduces navigation errors and enhances measurement reliability, supporting faster, more accurate clinical workflows.
March 2025 – OHIF/Viewers: Targeted 2D MPR navigation bug fix and supporting utility; improved measurement switching correctness and viewport selection across multiple viewports. This work reduces navigation errors and enhances measurement reliability, supporting faster, more accurate clinical workflows.
February 2025: OHIF/Viewers - Implemented a targeted fix to robustly handle measurement label customization for arrow-annotated measurements. By adding a getTextCallback check in the active tool options, measurement label auto-completion now behaves correctly for measurements following arrow annotations, eliminating incorrect labels and improving reliability of the measurement workflow. This change addresses issue #4739 and was implemented as a small, low-risk patch with clear commit history.
February 2025: OHIF/Viewers - Implemented a targeted fix to robustly handle measurement label customization for arrow-annotated measurements. By adding a getTextCallback check in the active tool options, measurement label auto-completion now behaves correctly for measurements following arrow annotations, eliminating incorrect labels and improving reliability of the measurement workflow. This change addresses issue #4739 and was implemented as a small, low-risk patch with clear commit history.
January 2025: OHIF/Viewers improvements focused on context menu reliability and visibility. By combining two commits, this work tightened accessibility for annotations and prevented clipping of context menus near viewport edges, leading to a smoother annotation workflow and better UX.
January 2025: OHIF/Viewers improvements focused on context menu reliability and visibility. By combining two commits, this work tightened accessibility for annotations and prevented clipping of context menus near viewport edges, leading to a smoother annotation workflow and better UX.
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