Level Set Techniques For Structural Inversion In Medical Imaging

2007 ◽  
pp. 61-90 ◽  
Author(s):  
Oliver Dorn ◽  
Dominique Lesselier
Keyword(s):  
Medical Imaging ◽  
Level Set ◽  
Structural Inversion

Retraction Notice: Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images

2018 ◽  
Vol 14 ◽  
Author(s):  
G. Elaiyaraja
Keyword(s):  
Medical Imaging ◽  
Level Set ◽  
Current Medical ◽  
Segmentation Algorithm ◽  
Scientific Publishing ◽  
Swarm Optimization ◽  
Original Source ◽  
Level Set Segmentation ◽  
Copyright Violation ◽  
Retraction Notice

The article entitled “Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images”, by G. Elaiyaraja, P. Epsiba, N. Kumaratharan and G. Suresh, has been retracted. Kindly see Bentham Science Policy on Article retraction at the link given below: (https://www.benthamscience.com/journals/current-medical-imaging/author-guidelines/). This article has been retracted on the request of the Editor. The authors have plagiarized a paper that had already been published in the journal Current Medical Imaging (CMIM) (Formerly: Current Medical Imaging Reviews) 14(3), Page: 389-400. http://www.eurekaselect.com/149444. It is a pre-requisite for authors to declare explicitly that their work is original and has not been published elsewhere. Authors are advised to properly cite the original source to avoid plagiarism and copyright violation. As such this article represents a severe abuse of the scientific publishing system. Bentham Science Publishers takes a very strong view on this matter and apologizes to the readers of the journal for any inconvenience this may cause.

scholarly journals Level-set techniques for microwave medical imaging

PAMM ◽  
2007 ◽  
Vol 7 (1) ◽  
pp. 1151601-1151602 ◽  
Author(s):  
Natalia Irishina ◽  
Oliver Dorn ◽  
Miguel Moscoso
Keyword(s):  
Medical Imaging ◽  
Level Set

scholarly journals Segmentation of Image Using Watershed and Fast Level set methods

2012 ◽  
pp. 38-43
Author(s):  
Minal M. Purani ◽  
Shobha Krishnan
Keyword(s):  
Medical Imaging ◽  
Level Set Method ◽  
Level Set ◽  
Medical Images ◽  
Level Set Methods ◽  
Initial Boundary ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Watershed Transform ◽  
Marching Method

Technology is proliferating. Many methods are used for medical imaging .The important methods used here are fast marching and level set in comparison with the watershed transform .Since watershed algorithm was applied to an image has over clusters in segmentation . Both methods are applied to segment the medical images. First, fast marching method is used to extract the rough contours. Then level set method is utilized to finely tune the initial boundary. Moreover, Traditional fast marching method was modified by the use of watershed transform. The method is feasible in medical imaging and deserves further research. It could be used to segment the white matter, brain tumor and other small and simple structured organs in CT and MR images. In the future, we will integrate level set method with statistical shape analysis to make it applicable to more kinds of medical images and have better robustness to noise.

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