CMIC Seminar: David Owen and Rene Lacher

Speaker: David Owen and Rene Lacher
UCL Contact: Dominique Drai (Visitors from outside UCL please email in advance).
Date/Time: 19 Jul 17, 13:00 - 14:00
Venue: Roberts 106

Abstract

David Owen

Title: Intelligent Imaging of Perfusion with Arterial Spin Labelling

Abstract: Arterial spin labelling (ASL) is a noninvasive MR technique for quantitative imaging of perfusion, which can be useful both for research and clinical use. In this talk, I will explore how ASL can be improved through the use of experimental design and information processing approaches. The aim of this work is to move ASL towards an "intelligent imaging" paradigm in which the image acquisition, reconstruction and processing are mutually coupled, and tailored to the individual patient.

Rene Lacher

Title: 3D breast surface reconstructions from consumer-grade RGBD cameras

Abstract: Breast cancer is one of the most prevalent yet increasingly treatable cancer types. Clinical studies are suggesting a significant impact of breast cancer treatment on female patients' wellbeing and quality of life. With the oncological prognosis for mastectomy being on par with breast-conserving surgery the latter still does lead to poor or suboptimal results in nearly a third of cases. Geometric 3D models of the breast have the potential to aid planning, assessment and prediction of treatment but require sustaining costly infrastructure-heavy commercial scanning solutions. This cross-disciplinary work, within the scope of a European project, investigates recently marketed depth consumer cameras as low-cost easy-to-operate imaging devices for dense 3D breast surface reconstruction. Clinical data acquisition software in accordance with a predefined protocol is implemented and deployed. Contemporary publicly available reconstruction frameworks from the computer vision and robotics community are being evaluated. Their shortcomings with respect to the characteristics of the captured breast data are addressed in a new tailored reconstruction pipeline and validated on synthetic, phantom and clinical data.