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Related Concept Videos

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Related Experiment Video

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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J³SPM AI: An integrated open-source platform for AI-assisted image analysis and image-guided workflows in scanning

SangHeon Lee1

  • 1School of Electronic-Mechanical Engineering, Robotics Engineering Major, Gyeongkuk National University, Gyungdongro 1375, Andong, Gyeongbuk 36729, Republic of Korea.

Micron (Oxford, England : 1993)
|March 14, 2026
PubMed
Summary

J³SPM artificial intelligence (AI) streamlines scanning probe microscopy (SPM) analysis by integrating AI tools into a user-friendly platform. This enhances image quality and throughput for nanometer-scale material characterization.

Keywords:
Atomic force microscopyDeep learningHigh-speed atomic force microscopyOpen sourceScanning probe microscopy

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Data Science

Background:

  • Scanning probe microscopy (SPM), especially atomic force microscopy (AFM), is crucial for nanoscale material characterization.
  • Existing SPM methods face challenges with image quality and throughput, limiting practical applications.
  • Advancements in automation have not fully resolved these persistent issues.

Purpose of the Study:

  • To develop an accessible platform for integrating artificial intelligence (AI) into SPM workflows.
  • To overcome limitations in image quality and throughput in SPM analyses.
  • To enable AI-assisted decision-making in SPM experiments.

Main Methods:

  • Development of J³SPM AI, an open-source, graphical user interface (GUI) platform.
  • Integration of AI tools for image preprocessing, dataset construction, model training, and inference.
  • Implementation of AI for object detection and region-of-interest identification to guide data acquisition.

Main Results:

  • J³SPM AI provides a unified environment for AI-assisted SPM analysis, eliminating the need for users to build machine learning pipelines.
  • The platform supports image-based object detection and region identification for targeted rescanning and data acquisition.
  • Successfully lowered the technical barrier for incorporating AI into SPM.

Conclusions:

  • J³SPM AI offers a practical framework for enhancing SPM experiments with AI-driven insights.
  • The platform facilitates AI-assisted decision-making, improving efficiency and data quality in nanoscale analysis.
  • Empowers researchers to leverage AI for advanced SPM applications without extensive machine learning expertise.