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Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
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Updated: Jul 29, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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One-Click-Based Perception for Interactive Image Segmentation.

Tao Wang, Haochen Li, Yuhui Zheng

    IEEE Transactions on Neural Networks and Learning Systems
    |May 19, 2023
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    Summary
    This summary is machine-generated.

    This study introduces a novel one-click interactive image segmentation method to reduce user effort. The approach achieves state-of-the-art accuracy with minimal clicks, improving efficiency in image segmentation tasks.

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    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Interactive image segmentation methods reduce user burden but often require excessive clicks for accurate results.
    • Existing deep learning approaches still face challenges in minimizing user interaction costs for precise segmentation.

    Purpose of the Study:

    • To develop an accurate interactive image segmentation approach that significantly minimizes user interaction.
    • To propose a one-click-based method for efficient and precise segmentation of targets.

    Main Methods:

    • A top-down framework is proposed, dividing the task into coarse localization and fine segmentation.
    • A two-stage interactive object localization network using object integrity (OI) and click centrality (CC) for accurate target enclosure.
    • A multilayer segmentation network with a diffusion module for enhanced layer information flow and precise perception.

    Main Results:

    • The proposed method achieves state-of-the-art performance on several benchmarks using only one click.
    • The two-stage localization network effectively reduces search space and enhances focus at higher resolutions.
    • The multilayer segmentation network accurately segments targets with minimal prior guidance.

    Conclusions:

    • The one-click interactive segmentation approach effectively minimizes user interaction cost while achieving high accuracy.
    • The framework is adaptable for multiobject segmentation tasks, demonstrating its versatility.
    • This method represents a significant advancement in efficient and user-friendly image segmentation.