Research Repository

See what's under the surface


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. (in press). Active vision and surface reconstruction for 3D plant shoot modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics,

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

Roots branch towards water by post-translational modification of transcription factor ARF7 (2018)
Journal Article
Orosa Puente, B., Leftley, N., Von Wangenheim, D., Banda, J., Anjil, S., Hill, K., …Bennett, M. (2018). Roots branch towards water by post-translational modification of transcription factor ARF7. 00 Journal not listed, 362(6421), 1407-1410. doi:10.1126/science.aau3956

Plants adapt to heterogeneous soil conditions by altering their root architecture. For example, roots branch when in contact with water using the hydropatterning response. We report that hydropatterning is dependent on auxin response factor ARF7. Thi... Read More

Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction (2018)
Journal Article
PRIDMORE, T., Gibbs, J., Pound, M., French, A., Wells, D., & Murchie, E. (2018). Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction. Plant Physiology, 178(2), 524-534. doi:10.1104/pp.18.00664

Three-dimensional (3D) computer-generated models of plants are urgently needed to support both phenotyping and simulation-based studies such as photosynthesis modelling. However, the construction of accurate 3D plant models is challenging as plants a... Read More

Towards low-cost image-based plant phenotyping using reduced-parameter CNN (2018)
Conference Proceeding
Atanbori, J., Chen, F., French, A. P., & Pridmore, T. (2018). Towards low-cost image-based plant phenotyping using reduced-parameter CNN

Segmentation is the core of most plant phenotyping applications. Current state-of-the-art plant phenotyping applications rely on deep Convolutional Neural Networks (CNNs). However, these networks have many layers and parameters, increasing training a... Read More

Cellular patterning of Arabidopsis roots under low phosphate conditions (2018)
Journal Article
Janes, G., von Wangenheim, D., Cowling, S., Kerr, I. D., Band, L. R., French, A. P., & Bishopp, A. (2018). Cellular patterning of Arabidopsis roots under low phosphate conditions. Frontiers in Plant Science, doi:10.3389/fpls.2018.00735. ISSN 1664-462X

Phosphorus is a crucial macronutrient for plants playing a critical role in many cellular signaling and energy cycling processes. In light of this, phosphorus acquisition efficiency is an important target trait for crop improvement, but it also provi... Read More

Enhancing supervised classifications with metamorphic relations (2018)
Conference Proceeding
Xu, L., Towey, D., French, A. P., Benford, S., Zhou, Z. Q., & Chen, T. Y. (2017). Enhancing supervised classifications with metamorphic relations. In MET '18: Proceedings of the 3rd International Workshop on Metamorphic Testing, 46-53. doi: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... Read More

Recognizing the presence of hidden visual markers in digital images (2017)
Conference Proceeding
Xu, L., French, A. P., Towey, D., & Benford, S. (2017). Recognizing the presence of hidden visual markers in digital images. In Proceedings of the on Thematic Workshops of ACM Multimedia 2017, 210-218. doi:10.1145/3126686.3126761

As the promise of Virtual and Augmented Reality (VR and AR) becomes more realistic, an interesting aspect of our enhanced living environment includes the availability — indeed the potential ubiquity — of scannable markers. Such markers could represen... Read More

Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress (2017)
Journal Article
Lowe, A., Harrison, N., & French, A. P. (2017). Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant Methods, 13, doi:10.1186/s13007-017-0233-z. ISSN 1746-4811

This review explores how imaging techniques are being developed with a focus on deployment for crop monitoring methods. Imaging applications are discussed in relation to both field and glasshouse-based plants, and techniques are sectioned into ‘healt... Read More

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping (2017)
Journal Article
Murchie, E. H., Wells, D. M., Jackson, A. S., Wilson, M. H., Townsend, A. J., Atkinson, J. A., …French, A. P. (2017). Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience, 6(10), doi:10.1093/gigascience/gix083

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation... Read More

Volume segmentation and analysis of biological materials using SuRVoS (Super-region Volume Segmentation) workbench (2017)
Journal Article
Darrow, M. C., Luengo, I., Basham, M., Spink, M. C., Irvine, S., French, A. P., …Duke, E. M. (2017). Volume segmentation and analysis of biological materials using SuRVoS (Super-region Volume Segmentation) workbench. Journal of Visualized Experiments, doi:10.3791/56162. ISSN 1940-087X

Segmentation is the process of isolating specific regions or objects within an imaged volume, so that further study can be undertaken on these areas of interest. When considering the analysis of complex biological systems, the segmentation of three-d... Read More

AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping (2017)
Journal Article
Pound, M. P., Fozard, S., Torres Torres, M., Forde, B. G., & French, A. P. (2017). AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping. Plant Methods, 13(1), doi:10.1186/s13007-017-0161-y. ISSN 1746-4811

Background: Computer-based phenotyping of plants has risen in importance in recent years. Whilst much software has been written to aid phenotyping using image analysis, to date the vast majority has been only semi-automatic. However, such interaction... Read More

SuRVoS: Super-Region Volume Segmentation workbench (2017)
Journal Article
Luengo, I., Darrow, M. C., Spink, M. C., Sun, Y., Dai, W., He, C. Y., …French, A. P. (2017). SuRVoS: Super-Region Volume Segmentation workbench. Journal of Structural Biology, 198(1), (43-53). doi:10.1016/j.jsb.2017.02.007. ISSN 1047-8477

Segmentation of biological volumes is a crucial step needed to fully analyse their scientific content. Not having access to convenient tools with which to segment or annotate the data means many biological volumes remain under-utilised. Automatic seg... Read More

Selective labeling: identifying representative sub-volumes for interactive segmentation (2016)
Journal Article
Luengo, I., Basham, M., & French, A. P. (in press). Selective labeling: identifying representative sub-volumes for interactive segmentation. Lecture Notes in Artificial Intelligence, 9993, doi:10.1007/978-3-319-47118-1_3. ISSN 0302-9743

Automatic segmentation of challenging biomedical volumes with multiple objects is still an open research field. Automatic approaches usually require a large amount of training data to be able to model the complex and often noisy appearance and struct... Read More

Approaches to three-dimensional reconstruction of plant shoot topology and geometry (2016)
Journal Article
Gibbs, J., Pound, M. P., French, A. P., Wells, D. M., Murchie, E. H., & Pridmore, T. P. (in press). Approaches to three-dimensional reconstruction of plant shoot topology and geometry. Functional Plant Biology, doi:10.1071/FP16167

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and... Read More

Deep machine learning provides state-of-the art performance in image-based plant phenotyping (2016)
Other
Pound, M. P., Burgess, A. J., Wilson, M. H., Atkinson, J. A., Griffiths, M., Jackson, A. S., …French, A. P. (2016). Deep machine learning provides state-of-the art performance in image-based plant phenotyping

Deep learning is an emerging field that promises unparalleled results on many data analysis problems. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping, and demonstrate state-of-th... Read More

A patch-based approach to 3D plant shoot phenotyping (2016)
Journal Article
Pound, M. P., French, A. P., Fozard, J. A., Murchie, E. H., & Pridmore, T. P. (2016). A patch-based approach to 3D plant shoot phenotyping. Machine Vision and Applications, 27(5), 767-779. doi:10.1007/s00138-016-0756-8

The emerging discipline of plant phenomics aims to measure key plant characteristics, or traits, though as yet the set of plant traits that should be measured by automated systems is not well defined. Methods capable of recovering generic representat... Read More

Fast global interactive volume segmentation with regional supervoxel descriptors (2016)
Conference Proceeding
Luengo, I., Basham, M., & French, A. P. (2016). Fast global interactive volume segmentation with regional supervoxel descriptors. In Medical Imaging 2016: Image Processingdoi:10.1117/12.2216382

In this paper we propose a novel approach towards fast multi-class volume segmentation that exploits supervoxels in order to reduce complexity, time and memory requirements. Current methods for biomedical image segmentation typically require either c... Read More

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), doi:10.1007/s00138-015-0737-3. ISSN 0932-8092

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