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Automatic Field-of-View Adjustment for a View-Expansive Microscope via LSTM-Based Gaze and Pipette Motion Interpretation

This paper presents an AI-driven automatic field-of-view adjustment system for a view-expansive microscope that utilizes an LSTM model to interpret pipette motion and operator gaze, significantly reducing ICSI procedure time and enabling novice operators to achieve expert-level speeds.

Original authors: Kenta Yokoe, Takuya Hara, Tadayoshi Aoyama

Published 2026-08-12
📖 1 min read☕ Coffee break read

Original authors: Kenta Yokoe, Takuya Hara, Tadayoshi Aoyama

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

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