
Lizepeng worked on the STOmics/cellbin2 repository, developing and refining core image processing and registration pipelines for large-scale spatial omics data. Over nine months, he delivered robust features such as chip-aware registration, multi-channel image alignment, and a unified stitching module, addressing challenges in data calibration and chip specification handling. His technical approach combined Python and C++ with libraries like OpenCV and NumPy, emphasizing modular design, compiled extensions, and multiprocessing for scalability. Lizepeng also improved configuration management, code documentation, and user feedback mechanisms, resulting in a maintainable, extensible codebase that supports accurate, high-throughput image analysis and streamlined contributor onboarding.

July 2025: Focused on documentation and usability improvements for the stitching function in STOmics/cellbin2, aligning developer experience with business value by enabling easier adoption and reducing runtime misconfigurations. No major bug fixes logged this month; emphasis was on documentation, code clarity, and cleanup to streamline maintenance.
July 2025: Focused on documentation and usability improvements for the stitching function in STOmics/cellbin2, aligning developer experience with business value by enabling easier adoption and reducing runtime misconfigurations. No major bug fixes logged this month; emphasis was on documentation, code clarity, and cleanup to streamline maintenance.
June 2025: Delivered core enhancements to the cellbin2 pipeline, focused on core stitching, data calibration, and multi-channel alignment, while tightening metadata handling and user feedback for heavy computations. These changes improve processing speed, data reliability, and extensibility for future features.
June 2025: Delivered core enhancements to the cellbin2 pipeline, focused on core stitching, data calibration, and multi-channel alignment, while tightening metadata handling and user feedback for heavy computations. These changes improve processing speed, data reliability, and extensibility for future features.
May 2025: Strengthened the STOmics/cellbin2 pipeline with robustness-driven feature work, configurability enhancements, and improved maintainability. The focus was on aligning the StereoChip module with evolving R&D requirements, enabling conditional workflow steps via configuration, and translating code comments for broader contributor accessibility. These changes reduce runtime issues, enable more flexible image analysis workflows, and shorten onboarding time for new contributors.
May 2025: Strengthened the STOmics/cellbin2 pipeline with robustness-driven feature work, configurability enhancements, and improved maintainability. The focus was on aligning the StereoChip module with evolving R&D requirements, enabling conditional workflow steps via configuration, and translating code comments for broader contributor accessibility. These changes reduce runtime issues, enable more flexible image analysis workflows, and shorten onboarding time for new contributors.
April 2025: Delivered the Stereo Chip Name Parsing and Management feature for STOmics/cellbin2, consolidating the chip naming system to reliably identify and display chip names, including handling of prefixes and sequence codes. Migrated parsing logic from Python to a compiled extension to improve performance and responsiveness. Streamlined the project by removing obsolete configuration files (chip_name.json) and simplifying the configuration surface. The work establishes a scalable foundation for chip-name management across platforms and future expansion.
April 2025: Delivered the Stereo Chip Name Parsing and Management feature for STOmics/cellbin2, consolidating the chip naming system to reliably identify and display chip names, including handling of prefixes and sequence codes. Migrated parsing logic from Python to a compiled extension to improve performance and responsiveness. Streamlined the project by removing obsolete configuration files (chip_name.json) and simplifying the configuration surface. The work establishes a scalable foundation for chip-name management across platforms and future expansion.
March 2025 performance summary for STOmics/cellbin2 focusing on registration pipeline improvements, chip-aware processing, and quality controls. Delivered key features for chip-integrated registration, robust image alignment, and expanded chip handling, alongside targeted bug fixes to ensure stability and reliability across pipelines. Resulting in higher data quality, fewer downstream errors, and clearer paths to scaling chip-aware analyses.
March 2025 performance summary for STOmics/cellbin2 focusing on registration pipeline improvements, chip-aware processing, and quality controls. Delivered key features for chip-integrated registration, robust image alignment, and expanded chip handling, alongside targeted bug fixes to ensure stability and reliability across pipelines. Resulting in higher data quality, fewer downstream errors, and clearer paths to scaling chip-aware analyses.
In Feb 2025, delivered enhancements to the Stitch module in STOmics/cellbin2, improved CLI for stereo data handling, added file-type parameters and overlap controls, fixed a down-sampling calculation bug in WSI stitching by using ceil to compute dimensions, and updated the README to reflect function signature changes. These changes improved data integrity, reproducibility, and user experience when stitching large whole-slide images and integrating stereo datasets.
In Feb 2025, delivered enhancements to the Stitch module in STOmics/cellbin2, improved CLI for stereo data handling, added file-type parameters and overlap controls, fixed a down-sampling calculation bug in WSI stitching by using ceil to compute dimensions, and updated the README to reflect function signature changes. These changes improved data integrity, reproducibility, and user experience when stitching large whole-slide images and integrating stereo datasets.
January 2025 (Month: 2025-01) - STOmics/cellbin2 delivered feature enhancements and robustness improvements to the image stitching and alignment workflows, with a focus on accuracy, reliability, and scalability. The work highlights a major upgrade to the stitching module, fixes for alignment padding, and stability improvements for template registration and chip detection, enabling higher-quality data and smoother downstream analysis.
January 2025 (Month: 2025-01) - STOmics/cellbin2 delivered feature enhancements and robustness improvements to the image stitching and alignment workflows, with a focus on accuracy, reliability, and scalability. The work highlights a major upgrade to the stitching module, fixes for alignment padding, and stability improvements for template registration and chip detection, enabling higher-quality data and smoother downstream analysis.
December 2024 monthly summary for STOmics/cellbin2: Implemented robust grayscale image processing and calibration alignment, stabilized HE image registration with QC-aware steps and HSV-based improvements, introduced anchor-based registration with enhanced transform controls, added template inference scaling with explicit FOV estimation, and developed an image stitching module with distribution packaging. These updates improve imaging workflow reliability, accuracy for high-resolution datasets, and enable end-to-end stitching capabilities, while delivering a ready-to-distribute solution.
December 2024 monthly summary for STOmics/cellbin2: Implemented robust grayscale image processing and calibration alignment, stabilized HE image registration with QC-aware steps and HSV-based improvements, introduced anchor-based registration with enhanced transform controls, added template inference scaling with explicit FOV estimation, and developed an image stitching module with distribution packaging. These updates improve imaging workflow reliability, accuracy for high-resolution datasets, and enable end-to-end stitching capabilities, while delivering a ready-to-distribute solution.
November 2024 (2024-11) monthly summary for STOmics/cellbin2: - Delivered major enhancements for large-chip detection and image processing to broaden data coverage and throughput. Features include downsampling of large images, support for non-square chip sizes, improved image loading for large files, and refined chip specification parsing. - Implemented robustness fixes across image processing and chip registration to improve reliability in real-world datasets. This includes fixes for scale search robustness, grayscale conversion before moments, stereo chip size handling, deprecated naming checks, and standardized grayscale preprocessing, with targeted improvements to the chip box registration workflow. - Overall impact: increased processing stability, expanded data handling capabilities, and reduced downstream rework, enabling more accurate chip analysis at scale. - Technologies and skills demonstrated: image processing pipelines, grayscale preprocessing, chip registration and alignment, robustness/fault-tolerance engineering, and focused bug-fix discipline.
November 2024 (2024-11) monthly summary for STOmics/cellbin2: - Delivered major enhancements for large-chip detection and image processing to broaden data coverage and throughput. Features include downsampling of large images, support for non-square chip sizes, improved image loading for large files, and refined chip specification parsing. - Implemented robustness fixes across image processing and chip registration to improve reliability in real-world datasets. This includes fixes for scale search robustness, grayscale conversion before moments, stereo chip size handling, deprecated naming checks, and standardized grayscale preprocessing, with targeted improvements to the chip box registration workflow. - Overall impact: increased processing stability, expanded data handling capabilities, and reduced downstream rework, enabling more accurate chip analysis at scale. - Technologies and skills demonstrated: image processing pipelines, grayscale preprocessing, chip registration and alignment, robustness/fault-tolerance engineering, and focused bug-fix discipline.
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