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15 October 2019 Denoising and contrast-enhancement approach of magnetic resonance imaging glioblastoma brain tumors
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We investigate a new preprocessing approach for MRI glioblastoma brain tumors. Based on combined denoising technique (bilateral filter) and contrast-enhancement technique (automatic contrast stretching based on image statistical information), the proposed approach offers competitive results while preserving the tumor region’s edges and original image’s brightness. In order to evaluate the proposed approach’s performance, quantitative evaluation has been realized through the Multimodal Brain Tumor Segmentation (BraTS 2015) dataset. A comparative study between the proposed method and four state-of-the art preprocessing algorithm attests that the proposed approach could yield a competitive performance for magnetic resonance brain glioblastomas tumor preprocessing. In fact, the result of this step of image preprocessing is very crucial for the efficiency of the remaining brain image processing steps: i.e., segmentation, classification, and reconstruction.

© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2019/$28.00 © 2019 SPIE
Hiba Mzoughi, Ines Njeh, Mohamed Ben Slima, Ahmed Ben Hamida, Chokri Mhiri, and Kheireddine Ben Mahfoudh "Denoising and contrast-enhancement approach of magnetic resonance imaging glioblastoma brain tumors," Journal of Medical Imaging 6(4), 044002 (15 October 2019).
Received: 14 March 2019; Accepted: 16 September 2019; Published: 15 October 2019

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