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

与传统的二维成像切片相比，三维解剖可视化已被证明可以提高定位结构的能力。这使得成像从主要的诊断工具转变为既可用于诊断又可用于手术计划的工具。为了允许对图像进行这种分割，需要执行每个体素按其性质进行标记，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，从而促进对解剖学的理解。由于学习和使用现有软件需要一定的时间，目前医学图像分割并没有广泛应用于临床实践。即使是训练有素的生物医学工程师，使用现有的软件对解剖结构进行分割也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。在概念验证研究期间的目标是：a)开发一种新的算法，以允许医学图像的交互式分割。b)使用最新的网络技术与基于web的软件进行交互。c)通过对接受肾癌手术的患者进行临床研究的细分来测试概念的证明。

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.