This advanced course on methods in bioimage analysis concentrates on teaching cutting-edge concepts and tools for quantitative image analysis and will seek to upgrade the competencies of future bioimage analysis experts on both theoretical algorithm advancements as well as on practical implementation skills.
The registration deadline for the DIASA course has been prolonged to March 25th, click here for more info. This is great opportunity to learn more about image analysis for scientific applications. Go to the course homepage and sign up!
We present TissUUmaps, browser-based tool for GPU-accelerated visualization and interactive exploration of tens of millions of datapoints overlaying tissue samples. Users can visualize markers and regions, explore spatial statistics and quantitative analyses of tissue morphology, and assess the quality of decoding in situ transcriptomics data. TissUUmaps provides instant multi-resolution image viewing, can be customized, shared, and also integrated in Jupyter Notebooks. It is also possible to directly connect spatial markers with markers in feature space, such as UMAP plots, to interactively relate feature space with physical space. TissUUmaps was created in collaboration between BIIF and the Wählby lab. You can read more about it and test the software on its web page: https://tissuumaps.github.io/
During the seminar, we will specifically showcase new features of TissUUmaps 3.1, such as: – HDF5 / AnnData files loading – Network diagram visualization – Multiple datasets displayed on a grid – Plugin engine
The webinar will be given by Christophe Avenel and Fredrik Nysjö.
The BioImage Informatics Facility (BIIF) together with microscopy expert Sylvie Le Guyader (LCI, Karolinska Institutet) organizes a Call4Help session every month. The aim is to offer combined expertise towards microscopy and bioimage analysis. All researchers from Swedish institutes can participate.
NMI node: BIIF at Uppsala University Location: on zoom Time of event: every 1st week of the month (mainly on Tuesdays, but there might be exceptions) Deadline for registration: continuous Weblink: https://www.scilifelab.se/call4help-form/ Contact email: biif@it.uu.se
This course is provided by the National BioInformatics Infrastructure Sweden (NBIS) and gives an introduction to the concept of Neural Networks (NN) and Deep Learning. Topics covered include: • NN building blocks, including concepts such as neurons, activation functions, loss functions, gradient descent and back-propagation • Convolutional Neural Networks • Recursive Neural Networks • Autoencoders • Best practices when designing NNs
The target group is PhD students from all subjects where digital image analysis (IA) is used as a research tool. No previous experience in IA is required from the course participants, but an interest in its potential as a tool in their own research is important. The course can be followed with a basic knowledge of mathematics (corresponding to upper‐ secondary level entry requirements) and basic computer skills.
