P-ResUnet: Segmentation of brain tissue with Purified Residual Unet

Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epilepsy, Alzheimer’s, and multiple sclerosis. Recently, UNet-like architectures are widely used for medical image segmentation, which achieved promising per...

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Veröffentlicht in:	Computers in biology and medicine 2022-12, Vol.151 (Pt B), p.106294-106294, Article 106294
Hauptverfasser:	Niu, Ke, Guo, Zhongmin, Peng, Xueping, Pei, Su
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Alzheimer's disease Biology Brain Brain - diagnostic imaging Brain research Coders Deep learning Epilepsy Fully convolutional network Humans Image acquisition Image processing Image Processing, Computer-Assisted - methods Image segmentation Information processing Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Medicine Metric space MRI Multiple sclerosis Neural networks Neural Networks, Computer Neuroimaging Neurological diseases Receptive field Semantics Tissues
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