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Interactive medical image segmentation software for preoperative planning of complex cancer surgeries

用于复杂癌症手术术前规划的交互式医学图像分割软件

基本信息

批准号：
710751
负责人：
金额：
$ 12.38万
依托单位：
INNERSIGHTLABS LTD
依托单位国家：
英国
项目类别：
GRD Proof of Concept
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=710751
关键词：
Interactive medical image segmentation software

项目摘要

The visualisation of anatomy in 3D has been shown to improve the ability to localizestructures when compared with traditional 2D imaging slices. This has allowed imaging tomove from a largely diagnostic tool to one that can be used for both diagnosis and operativeplanning.To allow for this segmentation of the images need to be performed, where each voxel islabeled by its nature i.e. extracting anatomical structures such as bones, lungs and otherorgans. This allows for better 3D visualisation and consequently facilitates understanding ofthe anatomy. Currently segmentation of medical images is not widely used in clinical practice,because of the time required to learn and use existing software. It can take several hours ofwork, even for a trained biomedical engineer, to perform a segmentation of anatomicalstructures using current available software. Also setting up the software for a few cases can beexpensive, and clinicians often do not have the computational resources to run thesealgorithms.The objective during the proof of concept study is to:a) Develop a novel algorithm to allow for an interactive segmentation of medical images.b) Make the interaction with the software web based, using the latest web technologies.c) Test the proof of concept by performing segmentations for a clinical study for patientsundergoing kidney cancer surgery.

与传统的2D成像切片相比，3D解剖结构的可视化已被证明可以提高定位结构的能力。这使得成像从一个主要的诊断工具转变为一个既可用于诊断又可用于手术计划的工具。为了实现这一点，需要对图像进行分割，其中每个体素都根据其性质进行标记，即提取解剖结构，如骨骼、肺和其他器官。这允许更好的3D可视化，从而有助于理解解剖结构。由于学习和使用现有的软件需要时间，目前医学图像的分割在临床实践中并没有得到广泛的应用。即使是训练有素的生物医学工程师，使用当前可用的软件执行解剖结构的分割也可能需要几个小时的工作。此外，为少数病例设置软件可能会很昂贵，临床医生通常没有计算资源来运行这些算法。概念验证研究期间的目标是：a）开发一种新的算法，以实现医学图像的交互式分割。B）使用最新的网络技术，基于网络与软件进行交互。c）通过对正在接受肾癌手术的患者进行临床研究的分割来测试概念验证。