Image Processing workshops

Quantify biological shape through a reproducible three-dimensional morphometrics workflow in 3D Slicer and R. Participants connect image acquisition and resolution to segmentation and cleaning, collect landmarks and semilandmarks, and derive shape variables using Procrustes alignment and sliding procedures. Statistical exercises use principal components and regression to interpret size and shape variation; visualisations include deformations, morphings and heatmaps. Live sessions: 9–13 November, 13:00–18:00 daily, Europe/Madrid (CET, UTC+01:00). Total 30 hours: 25 live plus five independent. English-language live online course; Fee €610; Ambassador Institution rate €488. VAT included. Capacity: 20. A Life Sciences degree and familiarity with R and geometric-morphometric concepts are expected. R/RStudio and 3D Slicer are required. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

Turn multispectral, hyperspectral and lidar observations into analysis-ready datasets with R. Using forest and ecological examples, participants assess metadata and data quality, correct geometric and radiometric errors, reduce noise, and derive spectral indices and structural features. Exercises connect temporal change analysis and classification with scale, accuracy and uncertainty, producing reproducible workflows for spatial research. 2026-11-10–2026-11-13, 12:00–16:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €420. Participants need basic competence and confidence in R and RStudio; prior remote-sensing experience is optional.

Build and evaluate deep-learning models for biological prediction using Python and Jupyter notebooks. Lectures and collaborative exercises develop convolutional networks for classification, regression and image segmentation, with attention to preprocessing, augmentation, class imbalance, cross-validation and overfitting. Later sessions explore learning-rate and training-duration choices, recurrent networks and applications to omics data. Participants interpret model performance and discuss their own research problems. 2026-11-23–2026-11-27, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €530. A biology background is expected; basic Python and Linux familiarity is helpful but not required.

This practical workshop trains structural biologists in cryoelectron tomography and subtomogram averaging using nextPYP, TomoBEAR and Warp/M, with teaching by the software developers. It follows the processing pipeline from tilt-series alignment and reconstruction through tomogram visualisation and archiving, manual and automated particle picking, extraction, subtomogram alignment and averaging, refinement and classification. Participants will build averaging projects and create three-dimensional maps. The workshop begins at 09:00 on 2 December and ends at 15:00 on 4 December 2026, Stockholm time (CET, UTC+1). No previous experience is required; bring a laptop and mouse. Selection considers applicants’ research projects and plans, with priority for current cryoET researchers and SciLifeLab cryo-EM facility users. Submit an application letter and CV by 23 October at 16:00; decisions are expected by 2 November, and payment is due 20 November. Fees are SEK 1,600 for academic participants and SEK 4,800 for industry. They cover three days of teaching, materials, lunches, refreshments, a certificate and the second-night dinner; travel and accommodation are additional.

Solve shape-analysis problems in R using measurements, landmarks and outlines. The programme develops data organisation and image processing before geometric transformations, alternative superimposition methods and Procrustes analysis. Participants visualise shape differences, test allometry and multivariate hypotheses, and compare principal-component, discriminant and regression approaches. Outline analysis introduces several Fourier representations and their statistical interpretation; participants can bring their own morphological datasets. Live sessions: 10, 11, 14, 15, 16, 17 and 18 December, 12:00–17:00, Europe/Madrid (CET, UTC+01:00). Total 40 hours: 35 live plus five independent. English-language live online course; Fee €495 until 31 October, then €565; Ambassador rates €396/€452. VAT included. Capacity: 16. Basic R, multivariate statistics and geometric morphometrics are recommended; this is not an introductory morphometrics course. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

This hands-on course trains microscopy image-analysis practitioners to apply deep learning to their own data and research problems. It addresses the gap between successful neural-network methods and the practical difficulties of training and deploying them. Applications span image restoration, classification and segmentation, object detection and morphological characterization, high-throughput imaging, and large-scale three-dimensional processing. The course focuses on practical use of these methods for microscopy rather than treating model development as a purely theoretical subject.

This practical course introduces spatial-omics methods, particularly multiplex immunofluorescence and spatial transcriptomics, and helps researchers choose suitable approaches for their questions. Hands-on sessions teach open-source imaging methods designed for cost-effective experiments. Training follows the full workflow from custom reagents and sample preparation to microscopy data acquisition, image processing and basic analysis. The intended participants are PhD students, postdocs and staff in tissue biology or biomedicine with experience in tissue handling, immunofluorescence and basic microscopy.