Daniel Sage
YOU?
Author Swipe
View article: Revisiting PSF models: Unifying framework and high‐performance implementation
Revisiting PSF models: Unifying framework and high‐performance implementation Open
Localisation microscopy often relies on detailed models of point‐spread functions. For applications such as deconvolution or PSF engineering, accurate models for light propagation in imaging systems with a high numerical aperture are requi…
View article: Roadmap on deep learning for microscopy
Roadmap on deep learning for microscopy Open
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep …
View article: SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model
SAMJ: Fast Image Annotation on ImageJ/Fiji via Segment Anything Model Open
Mask annotation remains a significant bottleneck in AI-driven biomedical image analysis due to its labor-intensive nature. To address this challenge, we introduce SAMJ, a user-friendly ImageJ/Fiji plugin leveraging the Segment Anything Mod…
View article: Revisiting PSF models: unifying framework and high-performance implementation
Revisiting PSF models: unifying framework and high-performance implementation Open
Localization microscopy often relies on detailed models of point spread functions. For applications such as deconvolution or PSF engineering, accurate models for light propagation in imaging systems with high numerical aperture are require…
View article: Machine learning in microscopy – insights, opportunities and challenges
Machine learning in microscopy – insights, opportunities and challenges Open
Machine learning (ML) is transforming the field of image processing and analysis, from automation of laborious tasks to open-ended exploration of visual patterns. This has striking implications for image-driven life science research, parti…
View article: Back to the future – 20 years of progress and developments in photonic microscopy and biological imaging
Back to the future – 20 years of progress and developments in photonic microscopy and biological imaging Open
In 2023, the ImaBio consortium (imabio-cnrs.fr), an interdisciplinary life microscopy research group at the Centre National de la Recherche Scientifique, celebrated its 20th anniversary. ImaBio contributes to the biological imaging communi…
View article: Surpassing light inhomogeneities in structured‐illumination microscopy with FlexSIM
Surpassing light inhomogeneities in structured‐illumination microscopy with FlexSIM Open
Super‐resolution structured‐illumination microscopy (SIM) is a powerful technique that allows one to surpass the diffraction limit by up to a factor two. Yet, its practical use is hampered by its sensitivity to imaging conditions which mak…
View article: Bridging the Gap: Integrating Cutting-edge Techniques into Biological Imaging with deepImageJ
Bridging the Gap: Integrating Cutting-edge Techniques into Biological Imaging with deepImageJ Open
This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in the life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained…
View article: Bridging the gap: Integrating cutting-edge techniques into biological imaging with deepImageJ
Bridging the gap: Integrating cutting-edge techniques into biological imaging with deepImageJ Open
This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained con…
View article: Surpassing Light Inhomogeneities in Structured-Illumination Microscopy with FlexSIM
Surpassing Light Inhomogeneities in Structured-Illumination Microscopy with FlexSIM Open
Super-resolution structured-illumination microscopy (SIM) is a powerful technique that allows one to surpass the diffraction limit by up to a factor two. Yet, its practical use is hampered by its sensitivity to imaging conditions which mak…
View article: JDLL: A library to run Deep Learning models on Java bioimage informatics platforms
JDLL: A library to run Deep Learning models on Java bioimage informatics platforms Open
We present JDLL, an agile Java library that offers a comprehensive toolset/API to unify the development of high-end applications of DL for bioimage analysis and to streamline their installation and maintenance. JDLL provides all the functi…
View article: Roadmap on Deep Learning for Microscopy
Roadmap on Deep Learning for Microscopy Open
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep …
View article: Biomedical image analysis competitions: The state of current participation practice
Biomedical image analysis competitions: The state of current participation practice Open
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the c…
View article: BioImage Model Zoo: A Community-Driven Resource for Accessible Deep Learning in BioImage Analysis
BioImage Model Zoo: A Community-Driven Resource for Accessible Deep Learning in BioImage Analysis Open
Deep learning-based approaches are revolutionizing imaging-driven scientific research. However, the accessibility and reproducibility of deep learning-based workflows for imaging scientists remain far from sufficient. Several tools have re…
View article: Steer’n’Detect: fast 2D template detection with accurate orientation estimation
Steer’n’Detect: fast 2D template detection with accurate orientation estimation Open
Motivation Rotated template matching is an efficient and versatile algorithm to analyze microscopy images, as it automates the detection of stereotypical structures, such as organelles that can appear at any orientation. Its performance ho…
View article: A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices
A Practical Guide to Supervised Deep Learning for Bioimage Analysis: Challenges and good practices Open
The variety of bioimage data and their quality have dramatically increased over the last decade. In parallel, the number of proposed deep learning (DL) models for their analysis grows by the day. Yet, the adequate reuse of published tools …
View article: Insights to the characterization of cell motility and intercellular communication through a bioimage analysis perspective
Insights to the characterization of cell motility and intercellular communication through a bioimage analysis perspective Open
DeepImageJ is a user-friendly solution that enables the generic use of pre-trained deep learn ing (DL) models for biomedical image analysis in ImageJ. The deepImageJ environment gives access to the largest bioimage repository of pre-traine…
View article: A framework for evaluating the performance of SMLM cluster analysis algorithms
A framework for evaluating the performance of SMLM cluster analysis algorithms Open
Single molecule localisation microscopy (SMLM) generates data in the form of Cartesian coordinates of localised fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has…
View article: Graphic: Graph-Based Hierarchical Clustering For Single-Molecule Localization Microscopy
Graphic: Graph-Based Hierarchical Clustering For Single-Molecule Localization Microscopy Open
We propose a novel method for the clustering of point-cloud data that originate from single-molecule localization microscopy (SMLM). Our scheme has the ability to infer a hierarchical structure from the data. It takes a particular relevanc…
View article: Optimal-Transport-Based Metric For SMLM
Optimal-Transport-Based Metric For SMLM Open
We propose the use of Flat Metric to assess the performance of reconstruction methods for single-molecule localization microscopy (SMLM) in scenarios where the ground-truth is available. Flat Metric is intimately related to the concept of …
View article: Correction of multiple-blinking artefacts in photoactivated localisation microscopy
Correction of multiple-blinking artefacts in photoactivated localisation microscopy Open
Photoactivated localisation microscopy (PALM) produces an array of localisation coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple-blinking and each protein is included …
View article: Graphic: Graph-Based Hierarchical Clustering for Single-Molecule Localization Microscopy
Graphic: Graph-Based Hierarchical Clustering for Single-Molecule Localization Microscopy Open
We propose a novel method for the clustering of point-cloud data that originate from single-molecule localization microscopy (SMLM). Our scheme has the ability to infer a hierarchical structure from the data. It takes a particular relevanc…
View article: Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features
Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features Open
Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, da…
View article: Optimal-transport-based metric for SMLM
Optimal-transport-based metric for SMLM Open
We propose the use of Flat Metric to assess the performance of reconstruction methods for single-molecule localization microscopy (SMLM) in scenarios where the ground-truth is available. Flat Metric is intimately related to the concept of …
View article: W2S: Widefield2SIM Raw Dataset
W2S: Widefield2SIM Raw Dataset Open
This dataset contains the raw images of W2S (https://arxiv.org/abs/2003.05961). W2S has 360 (120 FOV x 3 channels) sets of human cell images. Each image set contains 400 Widefield shots, 15 (3 phases x 5 shots) shots of SIM inputs and 1 SI…