Imaging & Mathematics Network

The Centre for Mathematical Imaging in Healthcare (CMIH) and Cancer Research UK Cambridge Institute (CRUK-CI) are creating a new Cambridge-wide network to bring together researchers in imaging and mathematics. We will discuss topics including imaging technologies, tools and methodologies, open problems and challenges associated with large volume or complex forms of imaging data.

Network meetings will take place once a term and will include talks from invited speakers. We encourage all attendees to come with questions and to actively participate in the discussion and networking session afterwards. Our intention is to bring imaging experts/users/researchers together to connect, share knowledge and to develop potential collaborations.

The Michaelmas network meeting will take place on Thursday 5th December from 3 – 4:30pm at Cancer Research UK Cambridge Institute.

Synopsis: Medical and Bio-Image Analysis: Tools & Methods
The advancement of imaging technologies over the past decade, has brought new computational challenges in order to deal with a large volume or complex forms of imaging data. During these talks, both speakers will review tools and useful methods to analyse and process such digital images (research & medical). They will introduce some of the well known commercial / open-source software and try to go through pros and cons associated with each approach.

The speakers for this meeting are:

Ali Dariush, PhD

An overview of open source software for scientific image analysis
As an astronomer working on medical image processing and in particular histopathology image analysis, I have to deal with various imaging data types acquired using different imaging systems e.g. microscopes, scanners etc. Such data covers a large range of modalities and depends upon the size and complexities of the data, it needs different strategies to analyse them accordingly. During my talk, I will review some of the tools I use on a daily basis to tackle such image analysis challenges. This, in particular, is very important to for creating customised pipelines and platforms in order to high-throughput analysis of large data volume while addressing specific scientific questions.

Ziqiang Huang, PhD

Cellular Pattern Recognition using Image Analysis
Computer Vision and Pattern Recognition are quite popular topics nowadays, and always interlinked. Here at CRUK-CI, we have tried a rather classical approach to differentiate cell phenotypes based on their nuclear fluorescent staining patterns. The goal of this project is to reduce or eliminate subjective judgement from the original pattern recognition task, and provide a quantitative platform that can be potentially extend, scaling up, and shaped to other applications in health research.

Download the poster Imaging and Mathematics 2019

Register here