Bio-inspired data mining and deep learning in biomedical image processing

Special Session 1


Behzad Aliahmad, Arcot Sowmya, Sridhar Arjunan


  • João Paulo Papa (Associate professor, São Paulo State University, Brazil)
  • Arcot Sowmya (Professor, School of Computer Science and Engineering, University of New South Wales (UNEW), Sydney, Australia)
  • Behzad Aliahmad (Dr, Research Staff Member, RMIT University, Melbourne, Australia)
  • Dwarikanath Mahapatra (Dr, Research Staff Member, Multimedia Analytics IBM Research, Melbourne, Australia)


Medical image analysis, Bio-inspired data mining, deep learning,


Our nature is full of inspirations and the recent research on medical image analysis has shifted towards biologically inspired or nature-driven algorithms to solve computationally challenging tasks as well as to improve the performance of the conventional algorithms. Examples include, object tracking using Cuckoo search and image segmentation by snake model. Another recent progress in this field has been made in the application of deep learning architecture to handle complex data mining tasks. However, in spite of such significant progress, there are still big challenges ahead for application of machine based analyses in practice. This special session aims to focus on the recent novelties in medical image processing and computational vision to be used in practice by clinicians. It will provide valuable insights into the advances in data mining approaches, novel concepts such as nature-inspired image processing algorithms and deep learning strategies in bioinformatics and discuss solutions to implementation challenges.

Other special sessions

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Breast Image Analysis
From Lab Technology to Clinical Applications: Latest Advances in Functional Near Infrared Spectroscopy (fNIRS)
Tele-Health: Assessing health with real-world constraints
Pediatric Neuroimaging