Magnetic Resonance Materials in Physics, Biology and Medicine - CALL FOR PAPERS
Special Issue on "The role of artificial intelligence in MRI/MRS acquisition and reconstruction"
The development of Artificial Intelligence (AI) and Machine Learning (ML) has evolved tremendously during the last decade. In the field of medical imaging, AI and ML have emerged as techniques that are likely to fundamentally transform clinical practice in the coming years. In particular, AI and ML have the potential to impact all stages of the imaging pipeline, from (1) image acquisition and reconstruction to (2) image analysis and interpretation and (3) diagnosis and prognosis.
A multitude of AI-based solutions have been presented over the last years. Recognizing this momentum, methods are evolving towards a clinical application and usage. Usability, robustness and reproducibility will play an increasing role when operating AI algorithms on a daily basis. Moreover, sensitivity and specificity of these AI solutions need to be ensured and validated for diverse and heterogeneous patient cohorts.
The aim of this special issue is to promote research that focuses on advancing AI for MR image acquisition. We invite submissions of original research that either fall within or expand AI-based solutions targeting at MRI/MRS acquisition and applications, such as but not limited to:
Development of novel application-specific AI-based solutions in for example image reconstruction, motion correction, sampling trajectory designDevelopment of novel multitask learning networks to jointly answer acquisition and reconstruction questions Development and validation of concepts that transfer, fine-tune, adapt or generalize methods to other imaging applications or organ systems to enhance the acquisition Development of clinical AI applications in MRI/MRS with a methodological emphasis
We invite manuscripts on topics pertinent to the scope of the Special Issue. In order to meet the time line, papers should be submitted not later than 1st October 2023 (and preferably sooner) using the normal submission procedures on the web (https://www.editorialmanager.com/mrmp/default1.aspx (this opens in a new tab)). Authors should indicate in their cover letter that the manuscript is submitted " The role of artificial intelligence in MRI/MRS acquisition and reconstruction”.
Qin Chen, Imperial College, London
Thomas Küstner, University Clinic, Tübingen
Lipeng Ning, Brigham and Womens’ Hospital, Harvard Medical School (Early Career Researcher)
Cian Scannell, Technical University Eindhoven (Early Career Researcher)
Changyu Sun, University of Missouri
David G Norris, Editor in Chief, Magma
Guest Editors of the Special Issue