Romain Fernandez - Academia.edu (original) (raw)

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Papers by Romain Fernandez

BackgroundHigh-throughput phenotyping is crucial for the genetic and molecular understanding of a... more BackgroundHigh-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge.ResultsWe designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D+t. The method was tested on a challenging Arabidopsis seedling dataset, including numer...

This dataset is delivered with the Fijiyama plugin for reviewing purpose and as unit tests. Howev... more This dataset is delivered with the Fijiyama plugin for reviewing purpose and as unit tests. However, this dataset could be useful for anyone starting processing image with Fijiyama.<br> More information at the official plugin page: https://imagej.net/Fijiyama

BackgroundHigh-throughput phenotyping platforms allow the study of the form and function of a lar... more BackgroundHigh-throughput phenotyping platforms allow the study of the form and function of a large number of genotypes subjected to different growing conditions (GxE). A number of image acquisition and processing pipelines have been developed to automate this process, for micro-plots in the field and for individual plants in controlled conditions. Capturing shoot development requires extracting from images both the evolution of the 3D plant architecture as a whole, and a temporal tracking of the growth of its organs.ResultsWe propose PhenoTrack3D, a new pipeline to extract a 3D+t reconstruction of maize at organ level from plant images. It allows the study of plant architecture and individual organ development over time during the entire growth cycle. PhenoTrack3D improves a former method limited to 3D reconstruction at a single time point [Artzet et al., 2019] by (i) a novel stem detection method based on deep-learning and (ii) a new and original multiple sequence alignment method...

ABSTRACTQuantification of healthy and degraded inner tissues in plants is of great interest in ag... more ABSTRACTQuantification of healthy and degraded inner tissues in plants is of great interest in agronomy, for example to assess plant’s health and quality, and to monitor physiological traits or diseases. But detecting functional and degraded tissues in-vivo, without harming the plant, is extremely challenging. In ligneous and perennial species, for which the sustainability of plantations is crucial, new solutions are needed. To tackle this challenge, we developed a novel approach based on multimodal 3D imaging and Artificial intelligence (AI)-based image processing that allowed a non-invasive diagnosis of inner tissues in living plants. The method was successfully applied to the grapevine (Vitis vinifera L.), whose vineyards’ sustainability is threatened by trunk diseases while the sanitary status of vines cannot be ascertained without injuring the plants. By combining MRI and X-ray CT 3D imaging, together with an automatic voxel classification, we were able to discriminate intact, ...

Test dataset and experimental results of the paper: <strong>"FijiRelax: Fast and noise... more Test dataset and experimental results of the paper: <strong>"FijiRelax: Fast and noise-corrected estimation of NMR relaxation maps in 3D + t".</strong>

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific r... more HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Reconstruction tridimensionnelle et suivi de lignées cellulaires à partir d’images de microscopie laser : application à des tissus végétaux Romain Fernandez

Bioinformatics

The increasing interest of animal and plant research communities for biomedical 3D imaging device... more The increasing interest of animal and plant research communities for biomedical 3D imaging devices results in the emergence of new topics. The anatomy, structure and function of tissues can be observed non-destructively in time-lapse multimodal imaging experiments by combining the outputs of imaging devices such as X-ray CT and MRI scans. However, living samples cannot remain in these devices for a long period. Manual positioning and natural growth of the living samples induce variations in the shape, position and orientation in the acquired images that require a preprocessing step of 3D registration prior to analyses. This registration step becomes more complex when combining observations from devices that highlight various tissue structures. Identifying image invariants over modalities is challenging and can result in intractable problems. Fijiyama, a Fiji plugin built upon biomedical registration algorithms, is aimed at non-specialists to facilitate automatic alignment of 3D imag...

Bioinformatics