Leonardo Campos is a Senior Software Engineer with 14 years of experience specializing in web-based medical imaging and DICOM ecosystems, currently at VIDA in Brazil. He blends deep full-stack JavaScript expertise with systems-level performance tuning—having built Electron processes for prefetching/decoding, optimized caching to cut series load times to milliseconds, and fixed critical memory leaks in cornerstonejs. A frequent contributor to cornerstonejs and the OHIF viewer, his open-source work spans back-end DICOM loaders and front-end annotation tools, including PET/CT false-color support and RECIST integration. He has driven production-grade imaging features like MPR, 4D playback, GPU-accelerated segmentation, and interactive reference-line workflows across commercial viewers. Comfortable in both startup and enterprise settings, he pairs architect-level thinking from earlier telecom and cloud-cost reduction projects with hands-on debugging and UI ergonomics. Colleagues rely on him for pragmatic, high-performance solutions in complex medical-imaging products.
JavaScript library to display interactive medical images including but not limited to DICOM
Role in this project:
Full-stack Developer
Contributions:5 commits, 3 PRs, 2 pushes in 1 year
Contributions summary:Leonardo's contributions focused on improving the image caching and color mapping features within the cornerstonejs library. They addressed a critical memory leak issue, ensuring proper rejection of promises during cache purging. Furthermore, the user introduced support for PET-CT studies with false color mapping and added relevant DICOM colormaps, enhancing the library's medical imaging capabilities. Their work also involved code refactoring and internal function adjustments related to canvas management.
OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages
Role in this project:
Front-end Developer
Contributions:37 reviews, 82 commits, 25 PRs in 5 months
Contributions summary:Leonardo primarily contributed to the front-end aspects of the OHIF viewer, focusing on user interface enhancements and feature implementations within the ReactJS framework. Their work involved addressing issues related to study list export workflows, and making improvements to the user experience, such as keyboard input for dialogs, and scalebars. They implemented the manual stack scroll synchronization and the integration of RECIST data within the measurement table and added a progress bar.
nci-qintrackermedicalreactjszero-footprint
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