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Atomic Force Microscopy

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

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In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

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Published on: July 24, 2020

动态意识深度预测自适应扫描光学连贯性断层扫描.

Dhyey Manish Rajani¹, Federico Seghizzi¹, Yang-Lun Lai¹

¹Department of Robotics, University of Michigan, USA.

Biomedical optics express

|January 16, 2025

概括

此摘要是机器生成的。

基于机器学习的自适应扫描克服了光学连贯断层扫描 (OCT) 中的分辨率速度权衡. 这种新的方法显著提高了高达40%的率,而不会牺牲图像质量.

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科学领域:

生物医学光学生物医学光学
医疗成像医学成像
机器学习在医学中的应用

背景情况:

传统的光学连贯性断层扫描 (OCT) 在图像分辨率和率之间面临着一个基本的权衡.
高分辨率的OCT成像通常受到缓慢的采集速度的限制,这阻碍了实时应用.

研究的目的:

开发和评估基于机器学习 (ML) 的自适应扫描方法,以克服海外和海外国家的率/分辨率权衡.
提高OCT扫描速度和通用性,以改善临床和外科应用.

主要方法:

提出了两个基于ML的自适应扫描管道,使用ConvLSTM和时间注意力单元 (TAU) 模型进行场景动态预测.
集成的ML模型与基于集群旅行销售员问题的动力学路径规划器.
使用确定性幻象和实时手术工具跟踪实验的验证技术.

主要成果:

与传统的光扫描和概率自适应扫描相比,实现了高达40%的平均速加快,而不会影响图像质量.
在各种场景中证明了更好的通用性,减少了手动系统参数调整的需要.
实时手术工具跟踪显示,与传统方法相比,平均加速度因子超过3.2倍.

结论:

基于ML的自适应扫描有效地解决了OCT的率/分辨率限制.
拟议的方法为包括手术在内的各种场合的OCT成像提供了增强的速度,通用性和稳定性.