Capsule Networks for Biomedical Pattern Analysis (CNBPA)

MOTIVATION

Capsule networks is emerging as a new and attractive deep learning network architecture in recent years, in terms of both their development and real-time applications. It deploys neurons into groups called capsules to efficiently learn and represent the biomedical patterns in various healthcare applications. With its ability to mimic the human’s three-dimensional perspective, it generalizes the obtained biomedical patterns to a greater degree from different viewpoints alongwith a considerably less amount of training data. With its integrated dynamic routing mechanism, capsule networks have delivered considerable results even for analysing small biomedical patterns. Especially, due to the advancement of initiating equivarince translation method instead of traditional translational invariance, it helps greatly to biomedical pattern analysis communities.

In the biomedical pattern analysis domain, capsule networks covers a wide range of areas like biomedical image analysis, medical diagnostics, DNA sequence analysis, biomedical data classification, disease identification and inspection. Capsule networks are able to inevitably capture and analyse the intricate biomedical patterns and extract the useful biomedical information out of the humongous volume of biomedical data that are currently available. This further emphasis the medical practitioners to make significant clinical decisions into existence. Despite the hype, the integration of capsule networks in biomedical pattern analysis still requires a broad community-wise discussion on initiating different innovative research ideas to foster the enhanced integration of capsule networks and biomedical pattern analysis.

This special issue aims to gather the state-of-the-art research works in the broad areas of biomedical pattern analysis and promote the implementation of capsule networks in biomedical domain.

List of Potential Topics include, but are not limited to:

• Deep learning for biomedical pattern analysis
• Capsules to perform genomic pattern analysis
• Capsule network based human face recognition techniques
• Capsules for biomedical data segmentation
• An ensemble of capsule networks for biomedical analysis
• Capsule networks for analysing human lung patterns
• Image based biological parameter extraction using capsule networks
• Integrated 3D vision for biomedical patter analysis
• Capsule based pattern analysis for biomedical knowledge discovery
• Capsule networks based proteomics
• Biomedical pattern visualization and analysis

IMPORTANT DATES

Submission Period – July 1-31, 2020

First review notification – September 5, 2020

First Revision Submission Deadline – October 10, 2020

Second review notification – November 15, 2020

Final Submission Deadline – December 30, 2020

Acceptance Notification – February 1, 2021

Publication – 2021

GUEST EDITORS

• Dr. P. Karrupusamy [Managing Guest Editor]

• Dr. Fernández-Caballero
• antonio.fdez@uclm.es

• Dr. Yong Shi,
• yshi5@kennesaw.edu

• Dr. Paval Lafta,
• lafatpav@fel.cvut.cz