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Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machines.

, , , , and . Int. J. Neural Syst., 15 (1-2): 1-11 (2005)

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Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging., , and . Neuroinformatics, 17 (4): 593-609 (2019)Difference of Gaussians revolved along elliptical paths for ultrasound fetal head segmentation., , , , , , and . Comput. Medical Imaging Graph., 38 (8): 774-784 (2014)Automatic independent component labeling for artifact removal in fMRI., , , , , and . NeuroImage, 39 (3): 1227-1245 (2008)Bayesian receiver operating characteristic metric for linear classifiers., , , and . Pattern Recognit. Lett., (2019)Adaptive edge detection based on 3D kernel functions for biomedical image analysis., , and . Image Processing: Algorithms and Systems, volume 5672 of SPIE Proceedings, page 224-235. SPIE, (2006)Face Prediction from fMRI Data during Movie Stimulus: Strategies for Feature Selection., , , , , and . ICANN (2), volume 6792 of Lecture Notes in Computer Science, page 189-196. Springer, (2011)Prediction of brain maturity based on cortical thickness at different spatial resolutions., , and . NeuroImage, (2015)Region-wise Loss for Biomedical Image Segmentation., and . CoRR, (2021)Automatic Quantification of Fluorescence from Clustered Targets in Microscope Images., , and . SCIA, volume 5575 of Lecture Notes in Computer Science, page 667-675. Springer, (2009)Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge., , , , , , , , , and 14 other author(s). IEEE Trans. Medical Imaging, 33 (4): 797-813 (2014)