Automated quantification of abnormalities associated with COVID-19 from chest CT could help clinicians evaluate the disease and assess its severity and progression. This study proposes measures of disease severity and a deep learning and deep reinforcement-based method to compute them.

There were significant differences in ADC50-300 between chronic pancreatitis and pancreatic carcinoma. Because D is not significantly different between groups, differences in ADC can be attributed mainly to differences in perfusion. The perfusion fraction f proved to be the superior DWI-derived parameter for differentiation of mass-forming pancreatitis and pancreatic carcinoma.

Using the IVIM-approach, the f value proved to be the best parameter for the differentiation between healthy pancreas and pancreatic cancer. The acquisition of several b-values strongly improved the stability of the parameter estimation thus increasing the sensitivity and specificity to 95.7% and 100% respectively. The proposed method may hold great promise for the non invasive, noncontrast-enhanced imaging of pancreas lesions and may eventually become a screening tool for pancreatic cancer.

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Focal cortical gyration anomalies can be detected at the early sulcation process stage. The process leading to abnormal gyration may evolve faster than physiologic ones and seems to be related to alterations of parenchymal layering occurring before 24 weeks' gestation. Most focal cortical gyration anomalies evolve toward what is currently considered polymicrogyria.