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CellProfiler Analyst Web (CPAW) - Exploration, analysis, and classification of biological images on the web | IEEE Conference Publication | IEEE Xplore

CellProfiler Analyst Web (CPAW) - Exploration, analysis, and classification of biological images on the web


Abstract:

CellProfiler Analyst (CPA) has enabled the scientific research community to explore image-based data and classify complex biological phenotypes through an interactive use...Show More

Abstract:

CellProfiler Analyst (CPA) has enabled the scientific research community to explore image-based data and classify complex biological phenotypes through an interactive user interface since its release in 2008. This paper describes CellProfiler Analyst Web (CPAW), a newly redesigned and web-based version of the software, allowing for greater accessibility, quicker setup, and facilitating a simple workflow for users. Installation and managing new versions has been challenging and time-consuming, historically. CPAW is an alternative that ensures installation and future updates are not a hassle to the user. CPAW ports the core iteration loop of CPA to a pure server-less browser environment using modern web-development technologies, allowing computationally heavy activities, like machine learning, to occur without freezing the user interface (UI). With a setup as simple as navigating to a website, CPAW presents a clean UI to the user to refine their classifier and explore pheno-typic data easily. We evaluated both the old and the new version of the software in an extensive domain expert study. We found that users could complete the essential classification tasks in CPAW and CPA 3.0 with the same efficiency. Additionally, users completed the tasks 20 percent faster using CPAW compared to CPA 3.0. The code of CellProfiler Analyst Web is open-source and available at https://mpsych.github.io/CellProfilerAnalystWeb/.
Date of Conference: 24-29 October 2021
Date Added to IEEE Xplore: 30 November 2021
ISBN Information:
Conference Location: New Orleans, LA, USA

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1 Introduction

Workflow through CellProfiler Analyst Web: The first step shows the data received from CellProfiler (left) with biological microscopy images of cells, then fetching cells to be trained in the second active learning step with tensorflow.js and classified by the machine learning classifier into its corresponding class. The third step shows the final scores ready for data exploration and analysis by the user. A demo of CellProfiler Analyst Web can be found here: https://mpsych.github.io/CellProfilerAnalystWeb/.

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