Our project: 'Hierarchical Analysis of Temporal and Spatial Image Data' will receive funding by SSF
9 Feb, 2017
Ola Spjuth is co-PI in the project ‘Hierarchical Analysis of Temporal and Spatial Image Data’ that received 29 MSEK from SSF for the period 2017-2021.
Abstract from the grant application:
Images contain very rich information, and digital cameras combined with image processing and analysis can detect and quantify a range of patterns and processes. The valuable information is however often sparse, and the ever increasing speed at which data is collected results in data-volumes that exceed the computational resources available. We herein propose a hierarchical approach to acquisition, analysis, and interpretation of image data. We will develop computationally efficient measurements for data description, confidence-driven machine learning for determination of ‘interestingness’, and a theory and framework to apply intelligent spatial and temporal information hierarchies, distributing data to computational resources and storage options based on low-level image features. We will focus our efforts on microscopy data, and work in three specific areas where image collection results in data volumes difficult to handle with today’s computational resources, namely (i) large-scale time-lapse experiments exploring the dynamics of cells and drug delivery particles in collaboration with Astra Zeneca, (ii), nanometer-resolution transmission electron microscopy data of in collaboration with Vironova AB, and (iii) multi-modal digital pathology data from SciLifeLab Sweden. We expect the resulting methodologies and frameworks to be highly relevant also for other scientific and industrial applications, including surveillance, predictive maintenance and quality control.