Boostlet.Js: Medical Image Processing Plugins for the Web via Javascript Injection

Can web-based image processing and visualization tools easily integrate into existing websites without significant time and effort? Our Boostlet.js library addresses this challenge by providing an open-source, JavaScript-based web framework to enable additional image processing functionalities. Boost-let examples include kernel filtering, image captioning, data visualization, segmentation, and web-optimized machine-learning models. To achieve this, Boostlet.js uses a browser bookmark to inject a user-friendly plugin selection tool called PowerBoost into any host website. Boostlet provides on-site access to a standard API independent of any visualization framework for pixel data and scene manipulation. Boostlet is natively integrated into SliceDrop, a web-based, interactive viewer for medical imaging data. Boostlets provide a modular architecture and client-side processing capabilities to apply advanced image-processing techniques using consumer-level hardware. The code is open-source and available.

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Publication Details

Published
2025-04-14
DOI
https://doi.org/10.1109/isbi60581.2025.10981020
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
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article

Boostlet.Js: Medical Image Processing Plugins for the Web via Javascript Injection

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Scientific Computing and Data Management
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Boostlet.Js: Medical Image Processing Plugins for the Web via Javascript Injection

SangHyuk Kim, Daniel Haehn, Tim De Meyer, Edward Gaibor, Vidhya Sree Narayanappa, Shruti Varade, Mahsa Geshvadi, Rohini Deshmukh
article en

Abstract

Can web-based image processing and visualization tools easily integrate into existing websites without significant time and effort? Our Boostlet.js library addresses this challenge by providing an open-source, JavaScript-based web framework to enable additional image processing functionalities. Boost-let examples include kernel filtering, image captioning, data visualization, segmentation, and web-optimized machine-learning models. To achieve this, Boostlet.js uses a browser bookmark to inject a user-friendly plugin selection tool called PowerBoost into any host website. Boostlet provides on-site access to a standard API independent of any visualization framework for pixel data and scene manipulation. Boostlet is natively integrated into SliceDrop, a web-based, interactive viewer for medical imaging data. Boostlets provide a modular architecture and client-side processing capabilities to apply advanced image-processing techniques using consumer-level hardware. The code is open-source and available.

University of Massachusetts Boston (US), Universität der Bundeswehr München (DE)
Openalex Percentile: Top 89%
Scientific Computing and Data Management
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