Outputs (21)

Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models (2022)
Journal Article
Ji, Y., Yang, S., Zhou, K., Lu, J., Wang, R., Rocliffe, H. R., …Huang, Z. (2022). Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models. Journal of Biomedical Optics, 27(8), Article 085002. https://doi.org/10.1117/1.JBO.27.8.085002

Aim: Morphological changes in the epidermis layer are critical for the diagnosis and assessment of various skin diseases. Due to its non-invasiveness, optical coherence tomography (OCT) is a good candidate for observing microstructural changes of ski... Read More about Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models.

Thermography for Disease Detection in Livestock: A Scoping Review (2022)
Journal Article
McManus, R., Boden, L., Weir, W., Viora, L., Barker, R., Kim, Y., …Yang, S. (2022). Thermography for Disease Detection in Livestock: A Scoping Review. Frontiers in Veterinary Science, 9, Article 965622. https://doi.org/10.3389/fvets.2022.965622

Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common standards or protocols for managing IRT parameters in animal disease detection r... Read More about Thermography for Disease Detection in Livestock: A Scoping Review.

Co-optimization method to improve lateral resolution in photoacoustic computed tomography (2022)
Journal Article
Zhang, Y., Yang, S., Xia, Z., Hou, R., Xu, B., Hou, L., …Xiong, J. (2022). Co-optimization method to improve lateral resolution in photoacoustic computed tomography. Biomedical Optics Express, 13(9), 4621-4636. https://doi.org/10.1364/BOE.469744

In biomedical imaging, photoacoustic computed tomography (PACT) has recently gained increased interest as this imaging technique has good optical contrast and depth of acoustic penetration. However, a spinning blur will be introduced during the image... Read More about Co-optimization method to improve lateral resolution in photoacoustic computed tomography.

Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography (2022)
Journal Article
Ji, Y., Yang, S., Zhou, K., Rocliffe, H. R., Pellicoro, A., Cash, J. L., …Huang, Z. (2022). Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography. Journal of Biomedical Optics, 27(1), https://doi.org/10.1117/1.JBO.27.1.015002

Significance: In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound... Read More about Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography.

Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning (2021)
Journal Article
Parra-Ullauri, J. M., Garcoa-Dominguez, A., Bencomo, N., Zheng, C., Zhen, C., Boubeta-Puig, J., …Yang, S. (2022). Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning. Software and Systems Modeling, 21, 1091-1113. https://doi.org/10.1007/s10270-021-00952-4

Modern software systems are increasingly expected to show higher degrees of autonomy and self-management to cope with uncertain and diverse situations. As a consequence, autonomous systems can exhibit unexpected and surprising behaviours. This is... Read More about Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning.

Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems (2021)
Journal Article
Zheng, C., Yang, S., Parra-Ullauri, J., Garcia-Dominguez, A., & Bencomo, N. (2022). Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(3), 479 - 488. https://doi.org/10.1109/TETCI.2021.3082204

Multi-agent systems deliver highly resilient and adaptable solutions for common problems in telecommunications, aerospace, and industrial robotics. However, achieving an optimal global goal remains a persistent obstacle for collaborative multi-agent... Read More about Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems.

The use of artificial intelligence and robotics in regional anaesthesia (2021)
Journal Article
McKendrick, M., Yang, S., & McLeod, G. A. (2021). The use of artificial intelligence and robotics in regional anaesthesia. Anaesthesia, 76(S1), 171-181. https://doi.org/10.1111/anae.15274

The current fourth industrial revolution is a distinct technological era characterised by the blurring of physics, computing and biology. The driver of change is data, powered by artificial intelligence. The UK National Health Service Topol Report em... Read More about The use of artificial intelligence and robotics in regional anaesthesia.

A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract (2020)
Journal Article
Yang, S., Lemke, C., Cox, B. F., Newton, I. P., Näthke, I., & Cochran, S. (2021). A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract. IEEE Transactions on Medical Imaging, 40(1), 38-47. https://doi.org/10.1109/tmi.2020.3021560

Inflammation of the gastrointestinal (GI) tract accompanies several diseases, including Crohn's disease. Currently, video capsule endoscopy and deep bowel enteroscopy are the main means for direct visualisation of the bowel surface. However, the use... Read More about A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract.

Hierarchical Radar Data Analysis for Activity and Personnel Recognition (2020)
Journal Article
Li, X., Li, Z., Fioranelli, F., Yang, S., Romain, O., & Kernec, J. L. (2020). Hierarchical Radar Data Analysis for Activity and Personnel Recognition. Remote Sensing, 12(14), Article 2237. https://doi.org/10.3390/rs12142237

Radar-based classification of human activities and gait have attracted significant attention with a large number of approaches proposed in terms of features and classification algorithms. A common approach in activity classification attempts to find... Read More about Hierarchical Radar Data Analysis for Activity and Personnel Recognition.

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy (2020)
Journal Article
Ali, S., Zhou, F., Braden, B., Bailey, A., Yang, S., Cheng, G., …Rittscher, J. (2020). An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific Reports, 10(1), Article 2748 (2020). https://doi.org/10.1038/s41598-020-59413-5

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art comput... Read More about An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.