Segmentation of Thoracic & Abdominal Anatomy Using Multi-Atlas Approach
Pooja Waghmare , Sunita P. Sagat, Mrs.M. D. Mali
Cite This Article:
Segmentation of Thoracic & Abdominal Anatomy Using Multi-Atlas ApproachInternational Journal of Innovative Research in Technology( ,ISSN: 2349-6002 ,Volume 6 ,Issue 4 ,Page(s):151-154 ,September 2019 ,Available :IJIRT148632_PAPER.pdf
Atlas segmentation; image registration; level sets, Multi Atlas Fusion.
Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large inter-patient variations are present. It shows that significant changes are needed to auto segment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple pre-segmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts
Article Details
Unique Paper ID: 148632

Publication Volume & Issue: Volume 6, Issue 4

Page(s): 151 - 154
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Last Date 25 January 2020

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