Image Analysis
The DCSR team is able to help you regarding image analysis topics.
The person involved in it is Arianna Ravera, Image Analysis and Machine Learning specialist.
Technical skills
Here are some topics on which 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 common when overlaying images.
Segmentation
Image processing technique of partitioning a digital image into multiple image segments, or regions of interest (ROIs). The goal is simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation can be a time-consuming task, and recent advances in Artificial Intelligence (AI) software techniques are making it easier for routine tasks to be completed.
Tracking
Automatic tracking of image content.
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 of the network will use math functions to solve a problem and send the output to subsequent layers. For example, in object detection each layer will be trained to identify a part of an image.
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).
Such models could be trained to identify x-ray images for example, and separate healthy vs unhealthy images.
U-Net: a Convolutional Networks for Biomedical Image Segmentation.
Softwares
If you are not interested or do not feel ready to experiment with ML techniques, to achieve your goals there are some software easy and intuitive.
For segmentation:
- ImageJ - https://imagej.net/imaging/segmentation
- Ilastik - https://www.ilastik.org
Contact & Terms of support
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* .
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Other contact: helpdesk@unil.ch with subject DCSR Image Analysis