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Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms.

Porcine health management

Hémonic A, Chauvin C, Delzescaux D, Verliat F, Corrégé I.
PMID: 29692925
Porcine Health Manag. 2018 Apr 17;4:8. doi: 10.1186/s40813-018-0084-7. eCollection 2018.

BACKGROUND: There has been a strong implication of both the French swine industry and the national authorities on reducing the use of antimicrobials in swine production since 2010. The annual monitoring of antimicrobial sales by the French Veterinary Medicines...

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Hémonic A, Chauvin C, Delzescaux D, et al. Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms. Porcine Health Manag. 2018;4:8doi: 10.1186/s40813-018-0084-7.
Hémonic, A., Chauvin, C., Delzescaux, D., Verliat, F., Corrégé, I. (2018). Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms. Porcine health management, 48. https://doi.org/10.1186/s40813-018-0084-7
Hémonic, Anne, et al. "Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms." Porcine health management vol. 4 (2018): 8. doi: https://doi.org/10.1186/s40813-018-0084-7
Hémonic A, Chauvin C, Delzescaux D, Verliat F, Corrégé I. Reliable estimation of antimicrobial use and its evolution between 2010 and 2013 in French swine farms. Porcine Health Manag. 2018 Apr 17;4:8. doi: 10.1186/s40813-018-0084-7. eCollection 2018. PMID: 29692925; PMCID: PMC5902966.
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A validation dataset for Macaque brain MRI segmentation.

Data in brief

Balbastre Y, Rivière D, Souedet N, Fischer C, Hérard AS, Williams S, Vandenberghe ME, Flament J, Aron-Badin R, Hantraye P, Mangin JF, Delzescaux T.
PMID: 29167818
Data Brief. 2017 Nov 04;16:37-42. doi: 10.1016/j.dib.2017.11.008. eCollection 2018 Feb.

Validation data for segmentation algorithms dedicated to preclinical images is fiercely lacking, especially when compared to the large number of databases of Human brain images and segmentations available to the academic community. Not only is such data essential for...

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Balbastre Y, Rivière D, Souedet N, et al. A validation dataset for Macaque brain MRI segmentation. Data Brief. 2017;16:37-42doi: 10.1016/j.dib.2017.11.008.
Balbastre, Y., Rivière, D., Souedet, N., Fischer, C., Hérard, A. S., Williams, S., Vandenberghe, M. E., Flament, J., Aron-Badin, R., Hantraye, P., Mangin, J. F., & Delzescaux, T. (2018). A validation dataset for Macaque brain MRI segmentation. Data in brief, 1637-42. https://doi.org/10.1016/j.dib.2017.11.008
Balbastre, Yaël, et al. "A validation dataset for Macaque brain MRI segmentation." Data in brief vol. 16 (2018): 37-42. doi: https://doi.org/10.1016/j.dib.2017.11.008
Balbastre Y, Rivière D, Souedet N, Fischer C, Hérard AS, Williams S, Vandenberghe ME, Flament J, Aron-Badin R, Hantraye P, Mangin JF, Delzescaux T. A validation dataset for Macaque brain MRI segmentation. Data Brief. 2017 Nov 04;16:37-42. doi: 10.1016/j.dib.2017.11.008. eCollection 2018 Feb. PMID: 29167818; PMCID: PMC5686468.
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Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain.

Scientific reports

Bouvier C, Souedet N, Levy J, Jan C, You Z, Herard AS, Mergoil G, Rodriguez BH, Clouchoux C, Delzescaux T.
PMID: 34836996
Sci Rep. 2021 Nov 26;11(1):22973. doi: 10.1038/s41598-021-02344-6.

In preclinical research, histology images are produced using powerful optical microscopes to digitize entire sections at cell scale. Quantification of stained tissue relies on machine learning driven segmentation. However, such methods require multiple additional information, or features, which are...

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Bouvier C, Souedet N, Levy J, et al. Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain. Sci Rep. 2021;11(1):22973doi: 10.1038/s41598-021-02344-6.
Bouvier, C., Souedet, N., Levy, J., Jan, C., You, Z., Herard, A. S., Mergoil, G., Rodriguez, B. H., Clouchoux, C., & Delzescaux, T. (2021). Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain. Scientific reports, 11(1), 22973. https://doi.org/10.1038/s41598-021-02344-6
Bouvier, C, et al. "Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain." Scientific reports vol. 11,1 (2021): 22973. doi: https://doi.org/10.1038/s41598-021-02344-6
Bouvier C, Souedet N, Levy J, Jan C, You Z, Herard AS, Mergoil G, Rodriguez BH, Clouchoux C, Delzescaux T. Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain. Sci Rep. 2021 Nov 26;11(1):22973. doi: 10.1038/s41598-021-02344-6. PMID: 34836996; PMCID: PMC8626511.
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Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T.
PMID: 34891872
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914.

Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning model relies on massive unbiased dataset...

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Wu H, Souedet N, You Z, et al. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2985-2988doi: 10.1109/EMBC46164.2021.9630914.
Wu, H., Souedet, N., You, Z., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20212985-2988. https://doi.org/10.1109/EMBC46164.2021.9630914
Wu, Huaqian, et al. "Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 2985-2988. doi: https://doi.org/10.1109/EMBC46164.2021.9630914
Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914. PMID: 34891872.
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Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images.

Frontiers in neuroanatomy

You Z, Balbastre Y, Bouvier C, Hérard AS, Gipchtein P, Hantraye P, Jan C, Souedet N, Delzescaux T.
PMID: 31920567
Front Neuroanat. 2019 Dec 17;13:98. doi: 10.3389/fnana.2019.00098. eCollection 2019.

In biomedical research, cell analysis is important to assess physiological and pathophysiological information. Virtual microscopy offers the unique possibility to study the compositions of tissues at a cellular scale. However, images acquired at such high spatial resolution are massive,...

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You Z, Balbastre Y, Bouvier C, et al. Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images. Front Neuroanat. 2019;13:98doi: 10.3389/fnana.2019.00098.
You, Z., Balbastre, Y., Bouvier, C., Hérard, A. S., Gipchtein, P., Hantraye, P., Jan, C., Souedet, N., & Delzescaux, T. (2019). Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images. Frontiers in neuroanatomy, 1398. https://doi.org/10.3389/fnana.2019.00098
You, Zhenzhen, et al. "Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images." Frontiers in neuroanatomy vol. 13 (2019): 98. doi: https://doi.org/10.3389/fnana.2019.00098
You Z, Balbastre Y, Bouvier C, Hérard AS, Gipchtein P, Hantraye P, Jan C, Souedet N, Delzescaux T. Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images. Front Neuroanat. 2019 Dec 17;13:98. doi: 10.3389/fnana.2019.00098. eCollection 2019. PMID: 31920567; PMCID: PMC6929681.
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Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Piluso S, Souedet N, Jan C, Clouchoux C, Delzescaux T.
PMID: 34891844
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2860-2863. doi: 10.1109/EMBC46164.2021.9631097.

A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is performed manually, becoming therefore tedious and subjective. Another option is...

Cite
Piluso S, Souedet N, Jan C, et al. Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2860-2863doi: 10.1109/EMBC46164.2021.9631097.
Piluso, S., Souedet, N., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20212860-2863. https://doi.org/10.1109/EMBC46164.2021.9631097
Piluso, Sebastien, et al. "Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 2860-2863. doi: https://doi.org/10.1109/EMBC46164.2021.9631097
Piluso S, Souedet N, Jan C, Clouchoux C, Delzescaux T. Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2860-2863. doi: 10.1109/EMBC46164.2021.9631097. PMID: 34891844.
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Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T.
PMID: 34891872
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914.

Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning model relies on massive unbiased dataset...

Cite
Wu H, Souedet N, You Z, et al. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2985-2988doi: 10.1109/EMBC46164.2021.9630914.
Wu, H., Souedet, N., You, Z., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20212985-2988. https://doi.org/10.1109/EMBC46164.2021.9630914
Wu, Huaqian, et al. "Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 2985-2988. doi: https://doi.org/10.1109/EMBC46164.2021.9630914
Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914. PMID: 34891872.
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In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy.

Frontiers in aging neuroscience

Santin MD, Vandenberghe ME, Herard AS, Pradier L, Cohen C, Debeir T, Delzescaux T, Rooney T, Dhenain M.
PMID: 27047372
Front Aging Neurosci. 2016 Mar 22;8:55. doi: 10.3389/fnagi.2016.00055. eCollection 2016.

Extracellular deposition of β amyloid plaques is an early event associated to Alzheimer's disease. Here, we have used in vivo gadolinium-stained high resolution (29(∗)29(∗)117 μm(3)) magnetic resonance imaging (MRI) to follow-up in a longitudinal way individual amyloid plaques in...

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Santin MD, Vandenberghe ME, Herard AS, et al. In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy. Front Aging Neurosci. 2016;8:55doi: 10.3389/fnagi.2016.00055.
Santin, M. D., Vandenberghe, M. E., Herard, A. S., Pradier, L., Cohen, C., Debeir, T., Delzescaux, T., Rooney, T., & Dhenain, M. (2016). In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy. Frontiers in aging neuroscience, 855. https://doi.org/10.3389/fnagi.2016.00055
Santin, Mathieu D, et al. "In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy." Frontiers in aging neuroscience vol. 8 (2016): 55. doi: https://doi.org/10.3389/fnagi.2016.00055
Santin MD, Vandenberghe ME, Herard AS, Pradier L, Cohen C, Debeir T, Delzescaux T, Rooney T, Dhenain M. In Vivo Detection of Amyloid Plaques by Gadolinium-Stained MRI Can Be Used to Demonstrate the Efficacy of an Anti-amyloid Immunotherapy. Front Aging Neurosci. 2016 Mar 22;8:55. doi: 10.3389/fnagi.2016.00055. eCollection 2016. PMID: 27047372; PMCID: PMC4802995.
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Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging.

Frontiers in neuroscience

Vandenberghe ME, Souedet N, Hérard AS, Ayral AM, Letronne F, Balbastre Y, Sadouni E, Hantraye P, Dhenain M, Frouin F, Lambert JC, Delzescaux T.
PMID: 30498427
Front Neurosci. 2018 Nov 15;12:754. doi: 10.3389/fnins.2018.00754. eCollection 2018.

Recently developed techniques to visualize immunostained tissues in 3D and in large samples have expanded the scope of microscopic investigations at the level of the whole brain. Here, we propose to adapt voxel-based statistical analysis to 3D high-resolution images...

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Vandenberghe ME, Souedet N, Hérard AS, et al. Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging. Front Neurosci. 2018;12:754doi: 10.3389/fnins.2018.00754.
Vandenberghe, M. E., Souedet, N., Hérard, A. S., Ayral, A. M., Letronne, F., Balbastre, Y., Sadouni, E., Hantraye, P., Dhenain, M., Frouin, F., Lambert, J. C., & Delzescaux, T. (2018). Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging. Frontiers in neuroscience, 12754. https://doi.org/10.3389/fnins.2018.00754
Vandenberghe, Michel E, et al. "Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging." Frontiers in neuroscience vol. 12 (2018): 754. doi: https://doi.org/10.3389/fnins.2018.00754
Vandenberghe ME, Souedet N, Hérard AS, Ayral AM, Letronne F, Balbastre Y, Sadouni E, Hantraye P, Dhenain M, Frouin F, Lambert JC, Delzescaux T. Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging. Front Neurosci. 2018 Nov 15;12:754. doi: 10.3389/fnins.2018.00754. eCollection 2018. PMID: 30498427; PMCID: PMC6250035.
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A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps.

Frontiers in neuroinformatics

Deruelle T, Kober F, Perles-Barbacaru A, Delzescaux T, Noblet V, Barbier EL, Dojat M.
PMID: 32508614
Front Neuroinform. 2020 May 19;14:22. doi: 10.3389/fninf.2020.00022. eCollection 2020.

Similarly to human population imaging, there are several well-founded motivations for animal population imaging, the most notable being the improvement of the validity of statistical results by pooling a sufficient number of animal data provided by different imaging centers....

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Deruelle T, Kober F, Perles-Barbacaru A, et al. A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps. Front Neuroinform. 2020;14:22doi: 10.3389/fninf.2020.00022.
Deruelle, T., Kober, F., Perles-Barbacaru, A., Delzescaux, T., Noblet, V., Barbier, E. L., & Dojat, M. (2020). A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps. Frontiers in neuroinformatics, 1422. https://doi.org/10.3389/fninf.2020.00022
Deruelle, Tristan, et al. "A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps." Frontiers in neuroinformatics vol. 14 (2020): 22. doi: https://doi.org/10.3389/fninf.2020.00022
Deruelle T, Kober F, Perles-Barbacaru A, Delzescaux T, Noblet V, Barbier EL, Dojat M. A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps. Front Neuroinform. 2020 May 19;14:22. doi: 10.3389/fninf.2020.00022. eCollection 2020. PMID: 32508614; PMCID: PMC7248563.
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Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T.
PMID: 34891872
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914.

Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning model relies on massive unbiased dataset...

Cite
Wu H, Souedet N, You Z, et al. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2985-2988doi: 10.1109/EMBC46164.2021.9630914.
Wu, H., Souedet, N., You, Z., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20212985-2988. https://doi.org/10.1109/EMBC46164.2021.9630914
Wu, Huaqian, et al. "Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 2985-2988. doi: https://doi.org/10.1109/EMBC46164.2021.9630914
Wu H, Souedet N, You Z, Jan C, Clouchoux C, Delzescaux T. Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2985-2988. doi: 10.1109/EMBC46164.2021.9630914. PMID: 34891872.
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Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Piluso S, Souedet N, Jan C, Clouchoux C, Delzescaux T.
PMID: 34891844
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2860-2863. doi: 10.1109/EMBC46164.2021.9631097.

A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is performed manually, becoming therefore tedious and subjective. Another option is...

Cite
Piluso S, Souedet N, Jan C, et al. Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:2860-2863doi: 10.1109/EMBC46164.2021.9631097.
Piluso, S., Souedet, N., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20212860-2863. https://doi.org/10.1109/EMBC46164.2021.9631097
Piluso, Sebastien, et al. "Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 2860-2863. doi: https://doi.org/10.1109/EMBC46164.2021.9631097
Piluso S, Souedet N, Jan C, Clouchoux C, Delzescaux T. Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2860-2863. doi: 10.1109/EMBC46164.2021.9631097. PMID: 34891844.
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Showing 1 to 12 of 13 entries