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The Centre for Medical Image Computing (CMIC) at University College London (UCL) hosted a two-day workshop on placenta imaging on April 12th and 13th 2018. The workshop consisted of 10 invited talks, 3 contributed talks, a poster session, a public interaction session and a panel discussion about the future direction of placental imaging. With approximately 50 placental researchers in attendance, the workshop was a platform for engineers, clinicians and medical experts in the field to network and exchange ideas. Attendees had the chance to explore over 20 posters with subjects ranging from the movement of blood within the placenta to the efficient segmentation of fetal MRI using deep learning tools. UCL public engagement specialists also presented a poster, encouraging attendees to learn more about how to engage patients and the public with their research, creating spaces for mutual learning and dialogue.

This project aims to create a computer-aided diagnosis (CAD) system that can be used to identify tuberculosis (TB) from chest radiographs (CXRs) and, in particular, to observe the progress of the disease where patients have had multiple images over a period of time. Such a CAD tool, if sufficiently automated could run in the background checking every CXR taken, regardless of whether the patient is a suspected carrier of TB. This paper outlines the first phase of the project: segmenting the lung region from a CXR. This is a challenge because of the variation in the appearance of the lung in different patients and even in images of the same patient.

This paper explains the hidden positive feedback in a two-stage fully differential amplifier through external feedback resistors and possible DC latch-up during the amplifier start-up. The biasing current selection among the cascade branches has been explained intuitively, with reference to previous literature. To avoid the latch-up problem, irrespective of the transistor bias currents, a novel hysteresis-based start-up circuit is proposed. An 87[Formula: see text]dB, 250[Formula: see text]MHz unity gain bandwidth amplifier has been developed in 65[Formula: see text]nm CMOS Technology and post-layout simulations demonstrate no start-up failures out of 1000 Monte-Carlo (6-Sigma) simulations. The circuit draws 126[Formula: see text][Formula: see text]A from a 1.2[Formula: see text]V supply and occupies the 2184[Formula: see text][Formula: see text]m2 area.

This paper presents a fully integrated front-end, low noise amplifier (LNA), dedicated to the processing of various types of bio-medical signals, such as Electrocardiogram (ECG), Electroencephalography (EEG), Axon Action Potential (AAP). A novel noise reduction technique, for an operational transconductance amplifier (OTA), has been proposed. This adds a current steering branch parallel to the differential pair, with a view to reducing the noise contribution by the cascode current sources. Hence, this reduces the overall input-referred noise of the LNA, without adding any additional power. The proposed technique implemented in 65[Formula: see text]nm CMOS technology achieves 30 dB closed-loop voltage gain, 0.05[Formula: see text]Hz lower cut-off frequency and 100 MHz 3-dB bandwidth. It operates at 1.2[Formula: see text]V power supply and draws 1[Formula: see text][Formula: see text]A static current. The prototype described in this paper occupies 3300[Formula: see text][Formula: see text]m2 silicon area.

The aim of this work is to investigate by modelling the possibility of reducing the operational energy of a typical house without negatively affecting its embodied energy. This is done through consideration of different building materials coupled with the use of an earth to air heat exchanger (EAHE) for fresh air supply and cooling. For known indoor and outdoor conditions and for given building materials (thermal capacity and conductance), a ventilation controller determines the amount of flow rate needed to temperate the indoor air temperature to achieve thermal comfort. Different wall configurations are assumed for each of the living zone and the bedroom zone of the apartment. It is found that the use of an optimal wall configuration in each zone coupled with the EAHE results in 76.7% energy savings compared with the reference case with conventional cooling.