Brain tumor segmentation approach based on the extreme learning machine and significantly fast and robust fuzzy C-means clustering algorithms running on Raspberry Pi hardware - ŞİŞİK, Fatih; SERT, Eser (Medical hypotheses, 2020)
Keywords: Algorithms; Brain - diagnostic imaging; Brain Neoplasms - diagnosis; Brain tumor segmentation; Cluster Analysis; Diagnosis, Computer-Assisted - instrumentation; Diagnosis, Computer-Assisted - methods; Extreme learning machine; Fuzzy Logic; Glioblastoma - diagnosis; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging; Neurons - metabolism; Raspberry Pi; Segmentation; Significantly fast and robust fuzzy C-means clustering; Software; Support Vector Machine; Brain tumor segmentation; Raspberry Pi; Extreme learning machine; Segmentation; Magnetic resonance imaging; Significantly fast and robust fuzzy C-means clustering