Deep Learning-Based Heart and Brain Sensing and Imaging
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 10 February 2025 | Viewed by 108
Special Issue Editor
Interests: IOTs and wearable devices; biomedical imaging and signal processing; bioelectromagnetism and medical applications; AI-based diagnosis of cardiac/neuro-electrical disorders
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The diagnosis and prognosis of conditions related to the human heart and brain in hospitals predominantly rely on medical images and sensor data; these medical data are processed in order for the doctor to study the patient’s cardiac and neurological condition and information. In order to address the large volume of medical data and improve the quality of healthcare services, more innovative technologies and intelligent systems for automatically and accurately detecting symptoms of diseases in their beginning stage are required.
The goal of this Special Issue is to present the latest research and high-quality advancements described by scholars and experts related to electrophysiological signaling and heart/brain image processing using computer pattern recognition and/or deep learning. This Special Issue will include papers pertaining to biomedical engineering, computer vision, and Internet of things, as well as the theoretical and practical aspects of various sensors and information theory in medical image processing.
Original research and review articles are welcome to be submitted for this Special Issue. Submitted papers should address the following topics, though this list is not exhaustive:
- ECG/EEG sensing and signal processing;
- Medical image processing related to the heart and brain;
- Bioinformatics for healthcare engineering;
- Supervised/unsupervised learning algorithms for ECG/EEG diagnosis applications;
- Explainable AI in ECG/EEG applications;
- Image retrieval, segmentation, grouping, and shaping;
- AI chips and their implementation of machine learning and deep learning algorithms;
- Internet of things (IOT);
- Applying machine learning-empowered sensing to industrial scenarios.
Prof. Dr. Dakun Lai
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- deep learning
- biomedical imaging
- electrophysiological signal
- heart
- brain
