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Patch Based Deep Local Feature Learning and Self Similarity Multi Level Clustering for Neonatal Brain Segmentation in MR Images
2019
International journal of recent technology and engineering
The main purpose of this work is to develop a new scheme to profoundly retrieving features to perform the process of identifying a brain regions from the MR neonatal brain image. First the input MR neonatal brain image is denoised by using the Modified Fuzzy Adaptive Non Local Mean Filter (FANLMF) and then the contrast of the image is enhanced using the Adaptive Average Intensity Based Histogram Equalization (AAIHE). After pre-processing the input MR image, the next step is to retrieve the
doi:10.35940/ijrte.d9579.118419
fatcat:hr4g54higbdxhe65s3fpjgkhyy