IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Sep 1, 2018
Classification of plants based on a multi-organ approach is very challenging. Although additional data provide more information that might help to disambiguate between species, the variability in shape and appearance in plant organs also raises the d...
Identifying distinctive subtypes of schizophrenia could ultimately enhance diagnostic and prognostic accuracy. We aimed to uncover neuroanatomical subtypes of chronic schizophrenia patients to test whether stratification can enhance computer-aided di...
Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its diagnosis and treatment selection of SZ. Evidence from neuroimaging has implicated disrupted functional connectivity in the pathophysiology. We aimed t...
Past work on relatively small, single-site studies using regional volumetry, and more recently machine learning methods, has shown that widespread structural brain abnormalities are prominent in schizophrenia. However, to be clinically useful, struct...
Annals of oncology : official journal of the European Society for Medical Oncology
Aug 1, 2018
BACKGROUND: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in th...
In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing ...
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