Authors who do not wish to share their data and materials must state that it will not be shared, and give the reason.
Full papers should describe original research work not previously published, and should be complete descriptions of full investigations.
The obtained quantitative features must be independent of the inter-subject variability and the type of medical device and, above all, must allow for reproducible results in the presence of high noise.
Type of papers The journal primarily publishes review articles deemed of interest to readers, as well as research articles, technical notes, and short communications relating to biomedical engineering in both the industrial, academic and clinical communities. However, these authors are still expected to make their data and materials available to reviewers on a confidential basis.
Most articles contain in-depth appraisals of the current state-of-the-art in a specific area of research or practice and provide complete and up-to-date bibliographies. Review articles should summarize current knowledge and historical information that has led to the current state-of-the-art.
The proposed deep learning algorithms should also ensure the independence of the results obtained by the operator of the imaging device and, to be more exact, its position relative to the patient or the parameter settings in the device.
Currently, almost every device intended for medical imaging has a more or less extended image and signal analysis and processing module which can use deep learning. In addition, the proposed deep learning algorithms must be tailored for the diagnosis of a specific disease entity.
Advances in neuroimaging: insights into neurological and psychiatric disease Call for papers: Deep learning in biomedical engineering Deep Learning in medicine is one of the most rapidly and new developing fields of science.
On the other hand, they must allow for reproducible results for high inter-subject variability. CRB will include submitted and invited contributions, which will be authored and peer reviewed by one or more independent experts in the field.