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Publications

by Keyword: Image processing

Narciso M, Otero J, Navajas D, Farré R, Almendros I, Gavara N, (2021). Image-based method to quantify decellularization of tissue sections International Journal Of Molecular Sciences 22,

Tissue decellularization is typically assessed through absorbance-based DNA quantification after tissue digestion. This method has several disadvantages, namely its destructive nature and inadequacy in experimental situations where tissue is scarce. Here, we present an image processing algorithm for quantitative analysis of DNA content in (de)cellularized tissues as a faster, simpler and more comprehensive alternative. Our method uses local entropy measurements of a phase contrast image to create a mask, which is then applied to corresponding nuclei labelled (UV) images to extract average fluorescence intensities as an estimate of DNA content. The method can be used on native or decellularized tissue to quantify DNA content, thus allowing quantitative assessment of decellularization procedures. We confirm that our new method yields results in line with those obtained using the standard DNA quantification method and that it is successful for both lung and heart tissues. We are also able to accurately obtain a timeline of decreasing DNA content with increased incubation time with a decellularizing agent. Finally, the identified masks can also be applied to additional fluorescence images of immunostained proteins such as collagen or elastin, thus allowing further image-based tissue characterization.

JTD Keywords: decellularization, differentiation, fluorescence image, image processing, microscopic image, Decellularization, Fluorescence image, Image processing, Matrix, Microscopic image, Segmentation


Vouloutsi, Vasiliki, Mura, Anna, Tauber, F., Speck, T., Prescott, T. J., Verschure, P., (2020). Biomimetic and Biohybrid Systems 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings , Springer, Cham (Lausanne, Switzerland) 12413, 1-428

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing


Martinez-Hernandez, Uriel, Vouloutsi, Vasiliki, Mura, Anna, Mangan, Michael, Asada, Minoru, Prescott, T. J., Verschure, P., (2019). Biomimetic and Biohybrid Systems 8th International Conference, Living Machines 2019, Nara, Japan, July 9–12, 2019, Proceedings , Springer, Cham (Lausanne, Switzerland) 11556, 1-384

This book constitutes the proceedings of the 8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019, held in Nara, Japan, in July 2019. The 26 full and 16 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Biomimetics, Computer architecture, Human robot interaction, Human-Computer Interaction (HCI), Humanoid robot, Image processing, Learning algorithms, Mobile robots, Multipurpose robots, Neural networks, Quadruped robots, Reinforcement learning, Robot learning, Robotics, Robots, Sensor, Sensors, Swarm robotics, User interfaces