Advances in Deep Learning for Histopathology
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (2 January 2022) | Viewed by 384
Special Issue Editors
Interests: neuromorphic engineering; embedded systems; FPGA; VLSI; robotics
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; medical image analysis
Special Issue Information
Dear Colleagues,
The use of computer-aided diagnosis systems and deep learning has had a huge impact in recent years. Computational advances and the direct application of convolutional neural networks to the biomedical field have led researchers to design smart systems for the automatic detection of malignancies and diseases in histopathological images. These systems and algorithms have already shown great potential and could play an important role in terms of reporting a second opinion and assisting doctors in specific image analysis tasks. This Special Issue is aimed at providing selected contributions on advances in deep learning applications to histopathology. Potential topics include but are not limited to: deep learning applications to medical image analysis, medical image processing with novel algorithms, computer-aided diagnosis systems, malignancy detection in histopathological images, and novel algorithms for processing and filtering histopathological images.
Prof. Dr. Alejandro Linares-Barranco
Dr. Lourdes Duran-Lopez
Dr. Saturnino Vicente-Diaz
Guest Editors
Manuscript Submission Information
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Keywords
- histopathology
- deep learning
- computer-aided diagnosis systems
- convolutional neural networks
- medical image analysis
