The SAMJ Annotator is a new plugin for ImageJ, Fiji, and Icy that offers user-friendly access to advanced image-segmentation models. These transformer-based models, including the Segment Anything Model (SAM) variants, have shown exceptional performance in segmenting complex and heterogeneous objects in natural images.
With SAMJ Annotator, users can easily annotate objects using manual prompts...
Join us for an engaging hands-on workshop at the Image to Knowledge Conference, where we will introduce participants to our collective efforts in the AI4Life project, a Horizon Europe-funded initiative to make AI tools accessible to the bioimage community and bridge the gap between life scientists and computational experts. This workshop brings the opportunity for participants to discover and...
This workshop will give an introduction into the ImageJ-based visual programming language JIPipe. Attendees will be guided step-by-step through the process of building batch processing workflows of ImageJ-functions and JIPipe-exclusive features. All demonstrations will be based on already published projects.
This session will provide hands-on experience with BiaPy's user-friendly workflows, zero-code notebooks, and Docker integration, empowering participants to tackle complex bioimage analysis tasks with ease. Whether you are a novice or an experienced developer, discover how BiaPy can streamline your image analysis processes and enhance your research capabilities in life sciences.
"The BioImage.IO Chatbot (https://github.com/bioimage-io/bioimageio-chatbot) is a chat assistant we created to empower the bioimaging community with state-of-the-art Large Language Models. Through the help of a series of extensions, the BioImage.IO Chatbot is able to query documentation and retrieve information from online databases and image.sc forum, as well as generating code and executing...
The clEsperanto project equips users and developers with GPU-accelerated image-processing components. It ships a library with which you will be able to build fast bioImage analysis scripts, by leveraging modern GPUs.
Positioned as a classical Image Processing library, it is built on a framework that makes it available in many language (Python, Java, C++), in many software platforms (Fiji,...
We will learn how to use conv-paint, a fast and interactive pixel classification tool for multi dimensional images. A graphical user interface is integrated into the image viewer napari, but we will also learn how to script the software from the python ecosystem. As a napari-plugin, conv-paint can easily be integrated with other plugins into complex image processing pipelines, even by users...
CAREamics is a modern re-implementation of widely used algorithms (CARE, N2N, N2V) and of more recent methods (DivNoising, HDN, muSplit, etc.), with a strong emphasis on usability for non-specialists. In this workshop, we will walk users through standard pipelines, how to approach a denoising task, which methods to choose and the various ways to use CAREamics, including via its napari UI.
DL4MicEverywhere is a platform that offers researchers an easy-to-use gateway to cutting-edge deep learning techniques for bioimage analysis. It features interactive Jupyter notebooks with user-friendly graphical interfaces that require no coding skills. The platform utilizes Docker containers to ensure portability and reproducibility, guaranteeing smooth operation across various computing...
This workshop will delve into the innovative features of NanoPyx, a Python framework designed to streamline microscopy image analysis. Participants will have hands-on experience on the image analysis methods implemented in NanoPyx, such as image registration, super-resolution and quality metrics, using the multiple user interfaces of NanoPyx: napari plugin, Jupyter notebooks and python...
We will introduce the IPA Project Template, which offers a structured way to organize image processing and analysis projects. Our template is designed to support users throughout their projects, providing space for experimentation, organizing proven methods into reproducible steps, tracking processing runs, and facilitating documentation.
During the workshop participants will create their...
The workshop will involve live coding, showing how one can use a Jupyter notebook for exploratory data analysis in napari and then make simple widgets based on that. The target is someone who has some familiarity with the napari application and bioimage analysis in Python and wants to take the next steps to customize/extend the napari GUI. For this, magicgui will be introduced as a way to...
In this workshop, we would like to introduce the functionalities of MemBrain v2 and demonstrate its handling using some showcase examples.
We will introduce MemBrain v2's three main components: MemBrain-seg is our out-of-the-box U-Net that gives good segmentations on a wide variety of tomograms. MemBrain-pick closely interacts with an annotation software to enable interactive training and...
In this interactive workshop, we will explore ultrack, a cutting-edge multi-hypothesis tracking framework designed for cell tracking across multiple microscopy modalities. Participants will begin by learning the core principles that drive ultrack's robust performance, including its ability to handle multiple input types such as intensity images, segmentation masks, contours or a combination of...
In this workshop, we will introduce users to CellProfiler, a software that allows you to create reproducible image analysis workflows without knowing how to code. Users will be introduced to how to input multi-channel data into CellProfiler, how to perform image processing, object finding, and measurement steps, as well as how to create reproducible outputs.
In this workshop, we will demonstrate Piximi, an images-to-discovery web application that allows users to perform deep learning without installation. We will demonstrate Piximi's ability to load images, run segmentation, perform classifications, and create measurements, all without the data leaving the user's computer.
We will present "motile" (https://funkelab.github.io/motile/) and its napari plugin for the tracking of objects in image sequences. The plugin allows users to go from a segmentation (e.g., of cells or nuclei) to a full tracking solution (e.g., a lineage tree) within a few clicks. Motile uses integer linear programs (ILPs) to solve tracking problems and comes with many useful costs and...
In this workshop, we present computational tools, workflows and pipelines for the processing and analysis of multiplexed tissue imaging data. In the first part of the workshop, we discuss commonly used analysis strategies and present a set of existing pipelines for multiplexed image processing, including MCMICRO (Schapiro et al., 2022), Steinbock (Windhager et al., 2023) and PIPEX...
In life sciences, tracking objects within movies is crucial for quantifying the behavior of particles, organelles, bacteria, cells, and entire organisms. However, tracking multiple objects across numerous movies and analyzing the objects’ movements can be challenging. This workshop aims to demonstrate the effective utilization of TrackMate for object tracking across multiple movies through...
In this workshop we propose to learn the principles of phasor analysis of Fluoresce Lifetime Microscopy (FLIM) data as well as to perform image analysis of FLIM data with this approach using (F)luorescence (L)ifetime (U)l(t)imate (E)xplorer (FLUTE) a new open source and user-friendly GUI that we recently developed [1,2]. Using FLUTE, participants will learn the basis of FLIM calibration,...
The workshop aims to introduce pymmcore-plus, a Python package designed for controlling microscopes via the open-source software Micro-Manager within a pure Python environment. It is an extension of pymmcore, the original Python 3.x bindings for the C++ Micro-Manager core and, as such, it operates independently of Java, eliminating the need for Java dependencies. Throughout the workshop, we'll...
QuPath is a popular open-source platform for visualizing, annotating and analyzing complex images - including whole slide and highly multiplexed datasets. It's especially useful for digital pathology applications, but can also be used for a wide range of other tasks (albeit mostly 2D... for now).
This work will introduce QuPath's main features, concepts and interface. It will show examples of...
QuPath is a popular open-source platform for visualizing, annotating and analyzing complex images - including whole slide and highly multiplexed datasets. QuPath is inspired and influenced by ImageJ and Fiji, but also quite different.
This workshop will show how experienced ImageJ and Fiji users can benefit from QuPath, and vice versa. It will show how to use ImageJ and QuPath together...
QuPath is a popular open-source platform for visualizing, annotating and analyzing complex images - including whole slide and highly multiplexed datasets. QuPath is written in Java and scriptable with Groovy, which makes it portable, powerful, and... sometimes a pain if you aren't a programmer. It can also be annoying if you are a programmer, but you find Groovy's syntax weird { and...
QuPath is a popular, open-source platform for visualizing, annotating and analyzing complex images - including whole slide and highly multiplexed datasets. QuPath is written in Java and scriptable with Groovy, which makes it portable, powerful, and... sometimes a pain if you'd rather be working in Python (sometimes we would too).
This workshop will show how QuPath and Python can work...
We - Jerome Mutterer and Jan Brocher - would like to introduce participants in this joint hands-on workshop to discover the flexible potential of ImageJ or Fiji alongside Inkscape for crafting scientific figures, slides, or posters. Our aim is not only to effectively incorporate traditional elements such as scale bars or labels but also to integrate reproducible content whenever possible. The...
ScaleFEx℠ is an open-source Python pipeline designed for extracting biologically relevant features from single cells in large image-based high-content imaging screens. Optimized for efficiency, it can easily handle datasets containing millions of images and several Tbs of data with reduced overhead and minimal redundancy. In our upcoming workshop, we will demonstrate how to install, configure,...
The workshop will show how Segment Anything, a deep learning model for interactive instance segmentation, can applied to segmentation and annotation tasks in biomedical images. We will first give an overview of different approaches that apply this method in the biomedical domain. Then we will introduce our tool, Segment Anything for Microscopy,
which introduces specialized models for...
The Segment Anything Model (SAM) by Meta is a transformer model trained on 11 million images and 1.1 billion masks, known for its exceptional generalization and zero-shot segmentation capabilities. In under a year, SAM has been cited in over 2,500 papers and has been widely adopted for specialized tasks like medical imaging and microscopy. This proposed course will provide hands-on guidance...
Based on the NEUBIAS (bio image analysts) and COMULIS (Correlated Multimodal Imaging in Life science) community effort, we have build a data base of image analysis software, aiming to be feed and used by the community. In this workshop, we will show how to search efficiently for an existing tool in bio image analysis, how to add a new tool or ressource and how to curate an existing entry,...
Our team has created TopoStats, an open-source Python toolkit for automated processing and analysis of Atomic Force Microscopy (AFM) images. We wish to provide a hands-on session to guide users through the TopoStats workflow, from raw AFM file formats through to molecule segmentation, quantification and biological interpretation. We will demonstrate how users can install TopoStats and discuss...
In this workshop we will go over basics of using BigTrace plugin to extract and analyze filament/vessel/neurite-like structures in large 3D multicolor (timelapse) datasets. It will be focused on volumetric dataset navigation, creation of ROIs and their analysis: measurements of intensity and geometrical properties, subvolume extraction and post-processing.
This hands-on workshop will introduce you to CytoDL, a powerful deep learning framework developed by the Allen Institute for Cell Science. CytoDL is designed to streamline the analysis of biological images, including 2D and 3D data represented as images, point clouds, and tabular formats. We will cover (A) Getting single cell and nucleus instance segmentations from image datasets from the...
The question "How thick is my biological object?" is more difficult to answer than it appears on first sight. In this workshop we will use different methods to calculate width profiles of 2D and 3D objects and learn about their differences. We will use FIJI/ImageJ in the workshop.
