5 July 2019, MI 03.13.010 The Coronary Atlas The coronary atlas is the largest collection of processed coronary angiogram images. Together with computational modelling, shape analysis and benchtop experiments these can reveal unique insights into our individual differences and why generic coronary artery disease treatment methods won’t always work. This thus not only forms a platform for optimising existing strategies but opens entire new pathways for preventive strategies through early prediction with medical biomarkers.
24 May 2019, MI 03.13.010 Invited Talk by Danielle Pace This work addresses the need for whole heart segmentation to individually label the cardiac chambers and great vessels for patients with congenital heart disease. Our main challenges are extreme anatomical variability and very limited training data. We demonstrate an iterative segmentation method, implemented as a recurrent neural network (RNN), in which a user provides a single landmark per structure, and a segmentation is evolved over multiple steps until reaching a stopping point that can be user-defined or automatically determined. The model grows segmentations in a predictable way that is defined during training. We show that a loss function that evaluates the entire sequence of output segmentations can be optimized using training images alongside input-output pairs of partial segmentations. Our experiments demonstrate that, compared to conventional models that segment an image in one step, the iterative segmentation offers better generalization to patients with the most severe heart malformations.
17 January 2019, MI HS 2 Invited Talk by Prof. Oliver Bimber Digital images play an essential role in our life. Advanced imaging systems, image processing methods, and visualization techniques are today fundamental to many professions. Medical imaging is certainly a good example. However, when mapping complex (possibly multidimensional) data to 2D, information is lost. What if the notion of digital images would change once and forever? What if instead of capturing, storing, processing and displaying only a single color per pixel, each pixel would consist of individual colors for each emitting direction? Digital images would no longer be two-dimensional matrices but four-dimensional ones (storing spatial information in two dimensions, and directional information in the other two dimensions). This is called a light field. I will introduce the fundamentals of light fields, explain how light fields are captured, processed, and displayed, and present several applications of light-field technology in various application domains, such as microscopy, sensors, and aerial scanning.
6 July 2018, MI 03.13.010 Invited Talk by Prof. William (Sandy) Wells Segmentation is a fundamental task for extracting semantically meaningful regions from an image. The goal of segmentation algorithms is to accurately assign object labels to each image location. However, image-noise, shortcomings of algorithms, and image ambiguities cause uncertainty in label assignment. Estimating the uncertainty in label assignment is important in multiple application domains, such as segmenting tumors from medical images for radiation treatment planning. One way to estimate these uncertainties is through the computation of posteriors of Bayesian models, which is computationally prohibitive for many practical applications. On the other hand, most computationally efficient methods fail to estimate label uncertainty. [...]
25 July 2019, Seoul, Korea 9 papers accepted at ICCV 2019 We are happy to announce that 8 papers of our chair will be presented at the International Conference on Computer Vision (ICCV 2019) in Seoul, Korea, October 27 - November 2, 2019.
6 July 2019, Shenzhen, China 13 papers accepted at MICCAI 2019 We are happy to announce that 13 papers of our chair will be presented at the 22nd International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2019) in Shenzhen, China, October 13-17, 2019.
28 February 2019, London, UK 1 paper accepted at MIDL 2019 We are happy to announce that one paper from our Chair will be presented at the International Conference on Medical Imaging with Deep Learning MIDL 2019, which will take place in London, July 8-9, 2019.
26 February 2019, Hong Kong 2 papers accepted at IPMI 2019 We are happy to announce that two papers from our Chair will be presented at the International Conference on Information Processing in Medical Imaging, IPMI 2019, which will take place in Hong Kong, June 2-7, 2019.
25 February 2019, Long Beach, CA, USA 5 papers accepted at CVPR 2019 We are happy to announce that five papers from our Chair will be presented at the International Conference on Computer Vision and Pattern Recognition, CVPR 2019, which will take place in Long Beach, CA, USA on June 16-20, 2019.