کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533393 870109 2012 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Neuro-levelset system based segmentation in dynamic susceptibility contrast enhanced and diffusion weighted magnetic resonance images
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Neuro-levelset system based segmentation in dynamic susceptibility contrast enhanced and diffusion weighted magnetic resonance images
چکیده انگلیسی

In this study, neuro-levelset method is proposed and evaluated for segmentation and grading of brain tumors on reconstructed images of dynamic susceptibility contrast (DSC) and diffusion weighted (DW) magnetic resonance images. The proposed neuro-levelset method comprises of two independent phases of processing. At first, reconstructed images have been independently processed by three different artificial neural network systems such as multilayer perceptron (MLP), self-organizing map (SOM), and radial basis function (RBF). The images used for these tasks were the cerebral blood volume (CBV), time to peak (TTP), percentage of base at peak (PBP) and apparent diffusion coefficient (ADC) images. This processing step ensued in formation of segmentation images of brain tumors. Further, in the second phase, these coarse segmented images of each artificial neural network system have been independently subjected as speed images to levelset method in order to optimize the segmentation performance. This has resulted in construction of three distinct neuro-levelset methods such as MLP-levelset, SOM-levelset and RBF-levelset method. Proposed neuro-levelset methods performed better in segmenting tumor, edema, necrosis, CSF and normal tissues as compared to independent artificial neural network systems. Among three neuro-levelset methods, RBF-levelset system has performed well with average sensitivity and specificity values of 91.43±2.94% and 94.43±1.90%, respectively.


► Neuro-levelset method is proposed and evaluated for segmentation and grading of brain tumors.
► MLP, SOM, RBF systems has been used as neural system.
► CBV, TTP, PBP and ADC images has been reconstructed and used as an input.
► RBF-levelset system has performed well with higher sensitivity and specificity values.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 45, Issue 9, September 2012, Pages 3501–3511
نویسندگان
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