Robotic Microtome Sectioning

机器人切片机

• 批准号: 2434612
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2434612
• 关键词: Robotic; Microtome; Sectioning

Each year 13 million histopathology slides are prepared in the UK for the purposes of clinical diagnosis, by 800 highly trained technicians with £40 Million NHA annual salary costs. 3 micron sections must be cut by hand from these fragile and precious biological samples for each slide. Many Pathology Departments carry large backlogs, delaying patient care, due to a shortage of trained technicians, a problem that could be solved by automation of this sectioning process. Automated sectioning would additionally improve slide quality, permitting rapid development of automated artificial intelligence solutions for pathological diagnosis, which are currently hampered by variability and poor quality of slides.The objective of this project is to conduct a feasibility study of automating all of the processes required for microtome sectioning. This objective can be achieved through the following research components:(1) Analysis of current processes, and automation feasibility(2) Theoretical analysis of robotic manipulation of biological samples(3) Development of demonstrators and performance analysis(4) Business case analysis and further exploitation of technologies developed

在英国，每年有1300万张组织病理学切片用于临床诊断，由800名训练有素的技术人员准备，年薪为4000万英镑。对于每个载玻片，必须从这些脆弱而珍贵的生物样品中手工切割3微米的切片。许多病理部门由于缺乏训练有素的技术人员而积压大量工作，延误了病人的护理，这一问题可以通过切片过程的自动化来解决。自动切片还将提高切片质量，从而快速开发用于病理诊断的自动化人工智能解决方案。目前，病理诊断因切片的可变性和质量差而受到阻碍。本项目的目标是对切片机切片所需的所有流程进行自动化的可行性研究。这一目标可以通过以下研究组成部分来实现：（1）分析当前流程和自动化可行性（2）对生物样品的机器人操作进行理论分析（3）开发演示程序和性能分析（4）业务案例分析和进一步利用所开发的技术

项目成果

Sensorized Skin With Biomimetic Tactility Features Based on Artificial Cross-Talk of Bimodal Resistive Sensory Inputs.

基于双峰电阻感觉输入的人工串扰的具有仿生触觉特征的传感皮肤。

• DOI: 10.17863/cam.98871
• 发表时间: 2023
• 作者: Georgopoulou A

Tactile perception in hydrogel-based robotic skins using data-driven electrical impedance tomography

• DOI: 10.1016/j.mtelec.2023.100032
• 发表时间: 2023-06-01
• 期刊: MATERIALS TODAY ELECTRONICS
• 作者: Hardman, David;Thuruthel, Thomas George;Iida, Fumiya
• 通讯作者: Iida, Fumiya