
Leonid Lunin contributed to PTB-MR/mrpro by modernizing its documentation pipeline, enabling direct rendering of Jupyter notebooks in Sphinx using myst-nb. He updated the CI workflow and configuration to streamline notebook integration, removing the need for manual HTML conversion and improving documentation accuracy and maintainability. In pytorch/ignite, Leonid extended the SSIM metric to support 3D tensors, enhancing volumetric data analysis for applications such as medical imaging. His work involved code refactoring, test updates, and integration of PyTorch-based image processing. Across both projects, Leonid demonstrated depth in Python, CI/CD, and documentation tooling, delivering targeted, maintainable engineering solutions.

March 2025: Delivered 3D SSIM support for volumetric data in pytorch/ignite, extending the SSIM metric to 3D tensors and updating tests to accommodate 3D inputs. This enhancement enables robust quality assessment for 3D models and volumetric data pipelines, expanding the library's applicability to medical imaging, 3D vision, and related workflows. The work is tracked with a single commit for traceability and maintainability.
March 2025: Delivered 3D SSIM support for volumetric data in pytorch/ignite, extending the SSIM metric to 3D tensors and updating tests to accommodate 3D inputs. This enhancement enables robust quality assessment for 3D models and volumetric data pipelines, expanding the library's applicability to medical imaging, 3D vision, and related workflows. The work is tracked with a single commit for traceability and maintainability.
Month: 2024-11. Key features delivered: Documentation: Enable rendering of Jupyter notebooks in docs. Major bugs fixed: None identified in 2024-11 for PTB-MR/mrpro. Overall impact and accomplishments: Modernized the documentation build by rendering .ipynb notebooks directly in Sphinx via myst-nb, reducing manual HTML conversion steps and aligning docs with current notebooks. This improves documentation accuracy, onboarding, and user guidance while speeding up the docs build. Technologies/skills demonstrated: myst-nb integration, Sphinx configuration, CI workflow automation, and general repository maintenance focused on documentation quality and build reliability.
Month: 2024-11. Key features delivered: Documentation: Enable rendering of Jupyter notebooks in docs. Major bugs fixed: None identified in 2024-11 for PTB-MR/mrpro. Overall impact and accomplishments: Modernized the documentation build by rendering .ipynb notebooks directly in Sphinx via myst-nb, reducing manual HTML conversion steps and aligning docs with current notebooks. This improves documentation accuracy, onboarding, and user guidance while speeding up the docs build. Technologies/skills demonstrated: myst-nb integration, Sphinx configuration, CI workflow automation, and general repository maintenance focused on documentation quality and build reliability.
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