All Outputs (16)

Addressing multiple salient object detection via dual-space long-range dependencies (2023)
Journal Article
Deng, B., French, A. P., & Pound, M. P. (2023). Addressing multiple salient object detection via dual-space long-range dependencies. Computer Vision and Image Understanding, 235, Article 103776. https://doi.org/10.1016/j.cviu.2023.103776

Salient object detection plays an important role in many downstream tasks. However, complex real-world scenes with varying scales and numbers of salient objects still pose a challenge. In this paper, we directly address the problem of detecting multi... Read More about Addressing multiple salient object detection via dual-space long-range dependencies.

Semantic Segmentation of Spontaneous Intracerebral Hemorrhage, Intraventricular Hemorrhage, and Associated Edema on CT Images Using Deep Learning (2022)
Journal Article
Kok, Y. E., Pszczolkowski, S., Law, Z. K., Ali, A., Krishnan, K., Bath, P., …French, A. P. (2022). Semantic Segmentation of Spontaneous Intracerebral Hemorrhage, Intraventricular Hemorrhage, and Associated Edema on CT Images Using Deep Learning. Radiology: Artificial Intelligence, 4(6), https://doi.org/10.1148/ryai.220096

This study evaluated deep learning algorithms for semantic segmentation and quantification of intracerebral hemorrhage (ICH), perihematomal edema (PHE), and intraventricular hemorrhage (IVH) on noncontrast CT scans of patients with spontaneous ICH. M... Read More about Semantic Segmentation of Spontaneous Intracerebral Hemorrhage, Intraventricular Hemorrhage, and Associated Edema on CT Images Using Deep Learning.

Domain Adaptation of Synthetic Images for Wheat Head Detection (2021)
Journal Article
Hartley, Z. K., & French, A. P. (2021). Domain Adaptation of Synthetic Images for Wheat Head Detection. Plants, 10(12), Article 2633. https://doi.org/10.3390/plants10122633

Wheat head detection is a core computer vision problem related to plant phenotyping that in recent years has seen increased interest as large-scale datasets have been made available for use in research. In deep learning problems with limited training... Read More about Domain Adaptation of Synthetic Images for Wheat Head Detection.

Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning (2020)
Journal Article
Khan, F. A., Voß, U., Pound, M. P., & French, A. P. (2020). Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning. Frontiers in Plant Science, 11, Article 1275. https://doi.org/10.3389/fpls.2020.01275

© Copyright © 2020 Khan, Voß, Pound and French. Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasing... Read More about Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning.

A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta) (2019)
Journal Article
Selvaraj, M. G., Montoya-P, M. E., Atanbori, J., French, A. P., & Pridmore, T. (2019). A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta). Plant Methods, 15(1), Article 131. https://doi.org/10.1186/s13007-019-0517-6

© 2019 The Author(s). Background: Root and tuber crops are becoming more important for their high source of carbohydrates, next to cereals. Despite their commercial impact, there are significant knowledge gaps about the environmental and inherent reg... Read More about A low-cost aeroponic phenotyping system for storage root development: Unravelling the below-ground secrets of cassava (Manihot esculenta).

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

Deep Hourglass for Brain Tumor Segmentation (2019)
Book Chapter
Benson, E., Pound, M. P., French, A. P., Jackson, A. S., & Pridmore, T. P. (2019). Deep Hourglass for Brain Tumor Segmentation. In BrainLes 2018: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (419-428). Springer. https://doi.org/10.1007/978-3-030-11726-9_37

The segmentation of a brain tumour in an MRI scan is a challenging task, in this paper we present our results for this problem via the BraTS 2018 challenge, consisting of 210 high grade glioma (HGG) and 75 low grade glioma (LGG) volumes for training.... Read More about Deep Hourglass for Brain Tumor Segmentation.

Enhancing supervised classifications with metamorphic relations (2018)
Presentation / Conference Contribution
Xu, L., Towey, D., French, A. P., Benford, S., Zhou, Z. Q., & Chen, T. Y. (2018). Enhancing supervised classifications with metamorphic relations. In MET '18: Proceedings of the 3rd International Workshop on Metamorphic Testing (46-53). https://doi.org/10.1145/3193977.3193978

We report on a novel use of metamorphic relations (MRs) in machine learning: instead of conducting metamorphic testing, we use MRs for the augmentation of the machine learning algorithms themselves. In particular, we report on how MRs can enable enha... Read More about Enhancing supervised classifications with metamorphic relations.

Root gravitropism: quantification, challenges, and solutions (2018)
Journal Article
Muller, L., Bennett, M. J., French, A., Wells, D. M., & Swarup, R. (2018). Root gravitropism: quantification, challenges, and solutions. Methods in Molecular Biology, 1761, 103-112. https://doi.org/10.1007/978-1-4939-7747-5_8

© 2018, Springer Science+Business Media, LLC. Better understanding of root traits such as root angle and root gravitropism will be crucial for development of crops with improved resource use efficiency. This chapter describes a high-throughput, autom... Read More about Root gravitropism: quantification, challenges, and solutions.

The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology (2017)
Journal Article
Burrell, T., Fozard, S., Holroyd, G. H., French, A. P., Pound, M. P., Bigley, C. J., …Forde, B. G. (2017). The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology. Plant Methods, 13(1), Article 10. https://doi.org/10.1186/s13007-017-0158-6

Background Chemical genetics provides a powerful alternative to conventional genetics for understanding gene function. However, its application to plants has been limited by the lack of a technology that allows detailed phenotyping of whole-seedling... Read More about The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology.

Leaf segmentation in plant phenotyping: a collation study (2015)
Journal Article
Scharr, H., Minervini, M., French, A. P., Klukas, C., Kramer, D. M., Liu, X., …Tsaftaris, S. A. (2016). Leaf segmentation in plant phenotyping: a collation study. Machine Vision and Applications, 27(4), 585-606. https://doi.org/10.1007/s00138-015-0737-3

Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Al... Read More about Leaf segmentation in plant phenotyping: a collation study.

Automated recovery of 3D models of plant shoots from multiple colour images (2014)
Journal Article
Pound, M. P., French, A. P., Murchie, E. H., & Pridmore, T. P. (2014). Automated recovery of 3D models of plant shoots from multiple colour images. Plant Physiology, 166(4), https://doi.org/10.1104/pp.114.248971

Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling.... Read More about Automated recovery of 3D models of plant shoots from multiple colour images.

Systems Analysis of Auxin Transport in the Arabidopsis Root Apex (2014)
Journal Article
Band, L. R., Wells, D. M., Fozard, J. A., Ghetiu, T., French, A. P., Pound, M. P., …Bennett, M. J. (2014). Systems Analysis of Auxin Transport in the Arabidopsis Root Apex. Plant Cell, 26(3), 862-875. https://doi.org/10.1105/tpc.113.119495

Auxin is a key regulator of plant growth and development. Within the root tip, auxin distribution plays a crucial role specifying developmental zones and coordinating tropic responses. Determining how the organ-scale auxin pattern is regulated at the... Read More about Systems Analysis of Auxin Transport in the Arabidopsis Root Apex.

Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending (2014)
Journal Article
Dyson, R. J., Vizcay-Barrena, G., Band, L. R., Fernandes, A. N., French, A. P., Fozard, J. A., …Jensen, O. E. (2014). Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending. New Phytologist, 202(4), 1212-1222. https://doi.org/10.1111/nph.12764

Root elongation and bending require the coordinated expansion of multiple cells of different types. These processes are regulated by the action of hormones that can target distinct cell layers. We use a mathematical model to characterise the influenc... Read More about Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending.

RootNav: navigating images of complex root architectures (2013)
Journal Article
Pound, M. P., French, A. P., Atkinson, J. A., Wells, D. M., Bennett, M. J., & Pridmore, T. (2013). RootNav: navigating images of complex root architectures. Plant Physiology, 162(4), 1802-1814. https://doi.org/10.1104/pp.113.221531

We present a novel image analysis tool that allows the semiautomated quantification of complex root system architectures in a range of plant species grown and imaged in a variety of ways. The automatic component of RootNav takes a top-down approach,... Read More about RootNav: navigating images of complex root architectures.

Developing digital records: Early experiences of record and replay (2006)
Journal Article
Crabtree, A., French, A., Greenhalgh, C., Benford, S., Cheverst, K., Fitton, D., …Graham, C. (2006). Developing digital records: Early experiences of record and replay. Computer Supported Cooperative Work, 15(4), 281-319. https://doi.org/10.1007/s10606-006-9026-z

In this paper we consider the development of 'digital records' to support ethnographic study of interaction and collaboration in ubiquitous computing environments and articulate the core concept of 'record and replay' through two case studies. One fo... Read More about Developing digital records: Early experiences of record and replay.