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Image Analysis

The DCSR team is able tocan help you regardingwith your image analysis topics.
pipeline.
The person involved in itthis is Arianna Ravera,Ravera, Image Analysis and Machine Learning specialist.

TechnicalSupport skillsOverview

From a quick question or a quick opinion, and a long project conceived and structured together. Everything related to extracting information and data from your images can be discussed together.

Here are some of the main topics on whichthat we can help.

Image Registration

Image processing technique used to align multiple scenes into a single integrated image. It helps overcome issues such as image rotation, scale, and skew that are commonusually whenasked overlaying images.

Screenshot 2022-12-01 at 14.54.17.pngabout:

Segmentation

  • Image pre-processing techniqueand ofenhancement
    • partitioning
  • Object a digital image into multiple image segments, or regions of interest (ROIs). The goal is simplifydetection and/or change the representation of an image intosegmentation
    • something
  • object thattracking
    • is
  • quantification more(shape, meaningfuldynamics, colocalization, and easierother toproperties)
    • analyze.
  • clustering Image/ segmentationclassifying canobjects
    • be a time-consuming task, and recent advances in Artificial Intelligence
  • visualization (AI)rendering softwarehigh-dimensional techniquesimages, are3D makingimages, itetc.)
    • easier
  • analytics for routine tasks to be completed.

image.png

Tracking

Automatic tracking of image content.

image.png

Deep Learning & Neural Networks

Neural networks are designed to mimic the human neural network and are used to develop models that can be used for a wide range of tasks such as image segmentation. They can also be used for traditional classical ML problems such as regression and classification.
The idea behind a neural network is to use layers of neurons to solve a problem. Each layer(statistics of the networkextracted willinformation). use
math
Usually functionsmost toof solvethe aanalyzes problemcarried out from us are programmed in Python as it is the most widespread programming language for the subject and sendis thevery outputfast toand subsequentadaptive. layers.(Please, Forif example,you're inalready objectfamiliar detectionwith eachPython, layervisit willthis bepage: trained to identify a part of an image.https://bioimagebook.github.io/index.html)
Because these neural networks and made up of many layers, they are also referred to as Deep Neural Networks (DNN) and the area of study is commonly referred to as Deep Learning (DL)But..
Such models could be trained to identify x-ray images for example, and separate healthy vs unhealthy images.

image.png

U-Net: a Convolutional Networks for Biomedical Image Segmentation.

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Softwares

If you are not interested or do not feel ready to experiment with MLcode, techniques, to achieve your goals youwe can use together some easy and intuitive software. Here some suggestions.
Here something you can checkout:
For segmentation:

Contact  &  Terms of support

Main contact:
We distinguish two kinds of support:
  • service mode: if you need quick help on a certain problem / if you need a suggestion, an information or similar - Submit a ticket to research-computing-fbm@unil.ch with subject: Service - *name of your department* .


  • project mode: if you have a more complex project that requires several days/weeks/months of work and you want to collaborate with us - Submit a ticket to research-computing-fbm@unil.ch with subject: Project - *name of your department* .
To stay tuned on: general info, scheduled events and meetings, and even to directly contact me,us, join our Team channel:

https://teams.microsoft.com/l/team/19%3aFeDnpOEAd5F_q4vM_JnZhLMpm-gGBt03gAYMflkvqIg1%40thread.tacv2/conversations?groupId=92e190bf-29ce-42cd-9a11-616e8b7f01fa&tenantId=25933cd5-fa42-4290-9edd-84c5831bcdd8

Other contact: helpdesk@unil.ch with subject DCSR Image Analysis

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