首页 | 本学科首页   官方微博 | 高级检索  
检索        


The segmentation of colorectal MRI images
Authors:Niranjan Joshi  Sarah Bond  Michael Brady
Institution:1. Mathematics for Real World Systems Centre for Doctoral Training, University of Warwick, Coventry, CV4 7AL, UK;2. Department of Computer Science, University of Warwick, UK;3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, China;4. Department of Pathology, University Hospitals Coventry and Warwickshire, Coventry, UK;5. The Alan Turing Institute, London, UK
Abstract:One of the key criteria that informs patient management decisions for colorectal cancer is the extent of the shortest distance from the edge of the primary tumour to the edge of the mesorectum, also referred to as circumferential resection margin (CRM). This region is resected during surgery. The CRM is difficult for clinicians to measure accurately, particularly from 2D slice data. We present a method for automatically calculating and visualising the CRM distances in colorectal cancer MR images. We use local phase of the monogenic signal calculated from the MR image intensities to find edge and ridge features within the data. A non-parametric mixture model is then used to describe image intensity values within level set framework in order to segment the mesorectal fascia and the corresponding tumour and lymph nodes, as distinct regions. This segmentation is used to provide an automatic analysis of the shortest distance resection margin, and we show that this is consistent with that of the clinically accepted MERCURY method. We use the segmentation to provide a 3D visualisation of where the resection margin is smallest. Finally, we reconstruct a 3D map of the segmented anatomy. Both the visualisation methods provide a useful tool to aid surgeons in their treatment planning.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号