Abdominal Imaging. Computation and Clinical Applications

Volume 8198 of the series Lecture Notes in Computer Science pp 290-298

A Survey of Cervix Segmentation Methods in Magnetic Resonance Images

  • Soumya GhoseAffiliated withCSIRO Computational Informatics
  • , Lois HollowayAffiliated withDepartment of Radiation Oncology, Liverpool HospitalInstitute of Medical Physics, Sydney UniversityCentre For Medical Radiation Physics, Northfields Ave, Wollongong NSW 2522, University of Wollongong
  • , Karen LimAffiliated withDepartment of Radiation Oncology, Liverpool Hospital
  • , Philip ChanAffiliated withRoyal Brisbane and Women’s Hospital
  • , Jacqueline VeeraAffiliated withDepartment of Radiation Oncology, Liverpool Hospital
  • , Shalini K. VinodAffiliated withDepartment of Radiation Oncology, Liverpool HospitalUniversity of Western SydneySouth Western Clinical School, University of NSW
  • , Gary LineyAffiliated withIngham Institute for Applied Medical Research, Liverpool Hospital
  • , Peter B. GreerAffiliated withDepartment of Radiation Oncology, Calvary Mater Newcastle HospitalDepartment of Physics, University of Newcastle
  • , Jason DowlingAffiliated withCSIRO Computational Informatics

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Radiotherapy is an effective therapy in the treatment of cervix cancer. However tumor and normal tissue motion and shape deformation of the cervix, the bladder and the rectum over the course of the treatment can limit the efficacy of radiotherapy and safe delivery of the dose. A number of studies have presented the potential benefits of adaptive radiotherapy for cervix cancer with high soft tissue contrast magnetic resonance images. To enable practical implementation of adaptive radiotherapy for the cervix, computer aided segmentation is necessary. Accurate computer aided automatic or semi-automatic segmentation of the cervix is a challenging task due to inter patient shape variation, soft tissue deformation, organ motion, and anatomical changes during the course of the treatment. This article reviews the methods developed for cervix segmentation in magnetic resonance images. The objective of this work is to present different methods for cervix segmentation in the literature highlighting their similarities, differences, strengths and weaknesses.


Cervix segmentation methods registration statistical shape models magnetic resonance imaging