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23 results on '"Cerrone, Lorenzo"'

1. SynCellFactory: Generative Data Augmentation for Cell Tracking

Author

Sturm, Moritz, Cerrone, Lorenzo, and Hamprecht, Fred A.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Cell tracking remains a pivotal yet challenging task in biomedical research. The full potential of deep learning for this purpose is often untapped due to the limited availability of comprehensive and varied training data sets. In this paper, we present SynCellFactory, a generative cell video augmentation. At the heart of SynCellFactory lies the ControlNet architecture, which has been fine-tuned to synthesize cell imagery with photorealistic accuracy in style and motion patterns. This technique enables the creation of synthetic yet realistic cell videos that mirror the complexity of authentic microscopy time-lapses. Our experiments demonstrate that SynCellFactory boosts the performance of well-established deep learning models for cell tracking, particularly when original training data is sparse.

Published
2024

2. CellTypeGraph: A New Geometric Computer Vision Benchmark

Author

Cerrone, Lorenzo, Vijayan, Athul, Mody, Tejasvinee, Schneitz, Kay, and Hamprecht, Fred A.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Classifying all cells in an organ is a relevant and difficult problem from plant developmental biology. We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries. To allow the convenient testing of new geometrical learning methods, the benchmark of Arabidopsis thaliana ovules is made available as a PyTorch data loader, along with a large number of precomputed features. Finally, we benchmark eight recent graph neural network architectures, finding that DeeperGCN currently works best on this problem.

Published
2022

3. End-to-End Learned Random Walker for Seeded Image Segmentation

Author

Cerrone, Lorenzo, Zeilmann, Alexander, and Hamprecht, Fred A.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We present an end-to-end learned algorithm for seeded segmentation. Our method is based on the Random Walker algorithm, where we predict the edge weights of the underlying graph using a convolutional neural network. This can be interpreted as learning context-dependent diffusivities for a linear diffusion process. Besides calculating the exact gradient for optimizing these diffusivities, we also propose simplifications that sparsely sample the gradient and still yield competitive results. The proposed method achieves the currently best results on a seeded version of the CREMI neuron segmentation challenge.

Published
2019

6. A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context.

Author

Vijayan, Athul, Mody, Tejasvinee Atul, Qin Yu, Wolny, Adrian, Cerrone, Lorenzo, Strauss, Soeren, Tsiantis, Miltos, Smith, Richard S., Hamprecht, Fred A., Kreshuk, Anna, and Schneitz, Kay

Subjects
PLANT cells & tissues, CELL analysis, NUCLEAR models, CELL nuclei, SOFTWARE visualization
Abstract

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We have developed an approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-tocell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading tool that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues. [ABSTRACT FROM AUTHOR]

Published
2024
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8. 3D UNet Arabidopsis Ovules ds3x

Author

Wolny, Adrian and Cerrone, Lorenzo

Subjects
Plantseg Unet 3d Semantic-Segmentation Arabidopsis Ovules Cell-Membrane Plant Tissue Fluorescence-Light-Microscopy Pytorch
Abstract

A a variant of 3D U-Net trained to predict the cell boundaries in confocal stacks of Arabidopsis ovules on 1/3-resolution in XY. Voxel size: (0.235, 0.225, 0.225µm^3) (ZYX). Trained on 3D confocal image stacks publishedhttps://elifesciences.org/articles/57613

Published
2023
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9. Designing Deep Learning Frameworks for Plant Biology

Author

Cerrone, Lorenzo

Subjects
004 Data processing Computer science, 570 Life sciences
Abstract

In recent years the parallel progress in high-throughput microscopy and deep learning drastically widened the landscape of possible research avenues in life sciences. In particular, combining high-resolution microscopic images and automated imaging pipelines powered by deep learning dramatically reduced the manual annotation work required for quantitative analysis. In this work, we will present two deep learning frameworks tailored to the needs of life scientists in the context of plant biology. First, we will introduce PlantSeg, a software for 2D and 3D instance segmentation. The PlantSeg pipeline contains several pre-trained models for different microscopy modalities and multiple popular graph-based instance segmentation algorithms. In the second part, we will present CellTypeGraph, a benchmark for quantitatively evaluating graph neural networks. The benchmark is designed to test the ability of machine learning methods to classify the types of cells in an \textit{Arabidopsis thaliana} ovules. CellTypeGraph's prime aim is to give a valuable tool to the geometric learning community, but at the same time it also offers a framework for plant biologists to perform fast and accurate cell type inference on new data.

Published
2023
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11. Microscopy‐based assay for semi‐quantitative detection of SARS‐CoV‐2 specific antibodies in human sera

Author

Pape, Constantin, Remme, Roman, Wolny, Adrian, Olberg, Sylvia, Wolf, Steffen, Cerrone, Lorenzo, Cortese, Mirko, Klaus, Severina, Lucic, Bojana, Ullrich, Stephanie, Anders‐Össwein, Maria, Wolf, Stefanie, Cerikan, Berati, Neufeldt, Christopher J., Ganter, Markus, Schnitzler, Paul, Merle, Uta, Lusic, Marina, Boulant, Steeve, Stanifer, Megan, Bartenschlager, Ralf, Hamprecht, Fred A., Kreshuk, Anna, Tischer, Christian, Kräusslich, Hans‐Georg, Müller, Barbara, and Laketa, Vibor

Subjects
General Biochemistry, Genetics and Molecular Biology
Published
2020
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17. Accurate and versatile 3D segmentation of plant tissues at cellular resolution

Author

Wolny, Adrian, primary, Cerrone, Lorenzo, additional, Vijayan, Athul, additional, Tofanelli, Rachele, additional, Barro, Amaya Vilches, additional, Louveaux, Marion, additional, Wenzl, Christian, additional, Strauss, Sören, additional, Wilson-Sánchez, David, additional, Lymbouridou, Rena, additional, Steigleder, Susanne S, additional, Pape, Constantin, additional, Bailoni, Alberto, additional, Duran-Nebreda, Salva, additional, Bassel, George W, additional, Lohmann, Jan U, additional, Tsiantis, Miltos, additional, Hamprecht, Fred A, additional, Schneitz, Kay, additional, Maizel, Alexis, additional, and Kreshuk, Anna, additional

Published
2020
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18. Author response: Accurate and versatile 3D segmentation of plant tissues at cellular resolution

Author

Wolny, Adrian, primary, Cerrone, Lorenzo, additional, Vijayan, Athul, additional, Tofanelli, Rachele, additional, Barro, Amaya Vilches, additional, Louveaux, Marion, additional, Wenzl, Christian, additional, Strauss, Sören, additional, Wilson-Sánchez, David, additional, Lymbouridou, Rena, additional, Steigleder, Susanne S, additional, Pape, Constantin, additional, Bailoni, Alberto, additional, Duran-Nebreda, Salva, additional, Bassel, George W, additional, Lohmann, Jan U, additional, Tsiantis, Miltos, additional, Hamprecht, Fred A, additional, Schneitz, Kay, additional, Maizel, Alexis, additional, and Kreshuk, Anna, additional

Published
2020
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19. Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera

Author

Pape, Constantin, primary, Remme, Roman, additional, Wolny, Adrian, additional, Olberg, Sylvia, additional, Wolf, Steffen, additional, Cerrone, Lorenzo, additional, Cortese, Mirko, additional, Klaus, Severina, additional, Lucic, Bojana, additional, Ullrich, Stephanie, additional, Anders-Össwein, Maria, additional, Wolf, Stefanie, additional, Cerikan, Berati, additional, Neufeldt, Christopher J., additional, Ganter, Markus, additional, Schnitzler, Paul, additional, Merle, Uta, additional, Lusic, Marina, additional, Boulant, Steeve, additional, Stanifer, Megan, additional, Bartenschlager, Ralf, additional, Hamprecht, Fred A., additional, Kreshuk, Anna, additional, Tischer, Christian, additional, Kräusslich, Hans-Georg, additional, Müller, Barbara, additional, and Laketa, Vibor, additional

Published
2020
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21. Microscopy‐based assay for semi‐quantitative detection of SARS‐CoV‐2 specific antibodies in human sera: A semi‐quantitative, high throughput, microscopy‐based assay expands existing approaches to measure SARS‐CoV‐2 specific antibody levels in human sera

Author

Pape, Constantin, Remme, Roman, Wolny, Adrian, Olberg, Sylvia, Wolf, Steffen, Cerrone, Lorenzo, Cortese, Mirko, Klaus, Severina, Lucic, Bojana, Ullrich, Stephanie, Anders‐Össwein, Maria, Wolf, Stefanie, Cerikan, Berati, Neufeldt, Christopher J., Ganter, Markus, Schnitzler, Paul, Merle, Uta, Lusic, Marina, Boulant, Steeve, and Stanifer, Megan

Subjects
SARS-CoV-2, IMMUNOGLOBULIN M, IMMUNOGLOBULINS, VIRUS diseases, HUMORAL immunity, STEREOLOGY, EMERGING infectious diseases
Abstract

Emergence of the novel pathogenic coronavirus SARS‐CoV‐2 and its rapid pandemic spread presents challenges that demand immediate attention. Here, we describe the development of a semi‐quantitative high‐content microscopy‐based assay for detection of three major classes (IgG, IgA, and IgM) of SARS‐CoV‐2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi‐automated image analysis workflow resulted in specific, sensitive and unbiased assay that complements the portfolio of SARS‐CoV‐2 serological assays. Sensitive, specific and quantitative serological assays are urgently needed for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high‐throughput microscopy to rapidly develop serological assays for emerging virus infections. [ABSTRACT FROM AUTHOR]

Published
2021
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22. Nephrogenic Diabetes Insipidus in Childhood

Author

Guarino, Stefano, primary, Diplomatico, Mario, additional, Marotta, Rosaria, additional, Pecoraro, Anna, additional, Furlan, Daniela, additional, Cerrone, Lorenzo, additional, Miraglia del Giudice, Emanuele, additional, Polito, Cesare, additional, La Manna, Angela, additional, and Marzuillo, Pierluigi, additional

Published
2018
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23. Nephrogenic Diabetes Insipidus in Childhood: Assessment of Volume Status and Appropriate Fluid Replenishment

Author

Lorenzo Cerrone, Emanuele Miraglia del Giudice, Rosaria Marotta, Anna Pecoraro, Stefano Guarino, Mario Diplomatico, Daniela Furlan, Angela La Manna, Cesare Polito, Pierluigi Marzuillo, Guarino, Stefano, Diplomatico, Mario, Marotta, Rosaria, Pecoraro, Anna, Furlan, Daniela, Cerrone, Lorenzo, Miraglia Del Giudice, Emanuele, Polito, Cesare, La Manna, Angela, and Marzuillo, Pierluigi

Subjects
Male, Fluid administration, Diabetes Insipidus, Nephrogenic, Thirst, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, 030225 pediatrics, medicine, Intravascular volume status, Humans, 030212 general & internal medicine, Dehydration, business.industry, Infant, General Medicine, Nephrogenic diabetes insipidus, medicine.disease, Anesthesia, Shock (circulatory), Pediatrics, Perinatology and Child Health, Diabetes insipidus, Emergency Medicine, Vomiting, Fluid Therapy, medicine.symptom, business
Abstract

Patients affected by nephrogenic diabetes insipidus (NDI) can present with hypernatremic dehydration, and first-line rehydration schemes are completely different from those largely applied in usual conditions determining a mild to severe hypovolemic dehydration/shock. In reporting the case of a patient affected by NDI and presenting with severe dehydration triggered by acute pharyngotonsillitis and vomiting, we want to underline the difficulties in managing this condition. Restoring the free-water plasma amount in patients affected by NDI may not be easy, but some key points can help in the first line management of these patients: (1) hypernatremic dehydration should always be suspected; (2) even in presence of severe dehydration, skin turgor may be normal and therefore the skinfold recoll should not be considered in the dehydration assessment; (3) decreased thirst is an important red flag for dehydration; (4) if an incontinent patient with NDI appears to be dehydrated, it is important to place the urethral catheter to accurately measure urine output and to be guided in parenteral fluid administration; (5) if the intravenous route is necessary, the more appropriate fluid replenishment is 5% dextrose in water with an infusion rate that should slightly exceed the urine output; (6) the 0.9% NaCl solution (10 mL/kg) should only be used to restore the volemia in a shocked NDI patient; and (7) it could be useful to stop indomethacin administration until complete restoration of hydration status to avoid a possible worsening of a potential prerenal acute renal failure.

Published
2020

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