/Imaging cells and tissues by electrical impedance tomography using high density active electrode array chips

Imaging cells and tissues by electrical impedance tomography using high density active electrode array chips

PhD - Leuven | More than two weeks ago

Use the power of high-density active electrode arrays to develop novel imaging methods for in-body imaging

Electrical impedance tomography is a non-invasive medical imaging technique developed in the 1980’s. It is typically used to discriminate tissues and has medical applications such as detection of cancer in skin, breast or cervix. The density of the electrodes used in these applications is currently low and spread over large area on the skin, and the scanned volume is typically large. This setting hampers sub-cellular resolution of the imaged structures. For in situ applications such as imaging inside the human body, and to detect subtle differences between cellular (sub)structures, higher density electrode configurations are needed. Imaging near surfaces of  surgical tools, brain probes or other implants could for example be used for imaging of lesions or tumors, or to characterize the tissue in general. Besides novel sensors/actuators also innovative reconstruction algorithms need to be developed to translate measured impedance profiles into images of the tissue structures. 

 

The candidate will explore how to actuate and reconstruct electrical fields by imec’s high density active electrode array chip platform. Further, this work will look at applying the tissue contrast measurement in relevant application such as brain organoid imaging and tumor discrimination, as well as cell migration. The PhD candidate will be embedded in the imec Life Sciences team and strongly interact with image reconstruction algorithm development teams at the University of Antwerp.

 

Required background: Electronic engineering

 

Type of work: 70% experimental, 20% modeling, 10% literature

Supervisor: Liesbet Lagae

Co-supervisor: Dries Braeken

Daily advisor: Saeedeh Ebrahimi Takalloo

The reference code for this position is 2022-088. Mention this reference code on your application form.