Classification of CT brain images based on deep learning networks

By Xiaohong W. Gao, Rui Hui, Zengmin Tian. Comput. Methods Programs Biomed., 2017

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Deep Learning in Neuroradiology (2018, background): “Gao et al 33 classified 285 noncontrast brain CT examinations with a deep network into 1 of 3 categories (normal aging, lesion [such as tumor], or Alzheimer disease [AD]).”
A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification (2019, methodology): “Classification of brain tumors from computed tomography (CT) images using deep learning methods such as multiple convolutional neural networks (CNNs) with discrimination method [9, 10] and single CNN method [11] have also been proposed.”
Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases (2021, unknown): “Deep learning efficiently generates models that produce more accurate results in predicting and classifying different diseases using images as in breast cancer [6], liver diseases [7], colon cancer [8], brain tumor [9], skin cancer [10], lung cancer [11], pneumonia [12], and recently COVID-19 diagno”
Applications of Deep Learning and Reinforcement Learning to Biological Data (2017, background): “, brain MRI [126], brain CT scans [135], and (f)MRIs [128]), and rheumatoid arthritis from hand radiographs [150].”