Objective. Pneumonia is the single largest cause of death in children worldwide due to infectious diseases. According to WHO guidelines, fast breathing and chest indrawing are the key indicators of pneumonia in children requiring antibiotic treatments. The aim of this study was to develop a video based novel method for simultaneous monitoring of respiratory rate and chest indrawing without upsetting babies. Approach. Respiratory signals, corresponding to periodic movements of chest-abdominal walls during breathing, were extracted by analyzing RGB (red, green, blue) components in video frames captured by a smartphone camera. Respiratory rate was then obtained by applying fast Fourier transform on the de-noised respiratory signal. Chest indrawing was detected by analysing relative phases of regional chest-abdominal wall mobility. The performance of the developed algorithm was evaluated on both healthy and pneumonia children. Main results. The proposed method can measure respiratory rate with an overall mean absolute error of 1.8 bpm in the range 18–105 bpm. Phase difference between regional chest wall movements in the chest indrawing (pneumonia) cases was found to be 143 ± 23.9 degrees, which was significantly higher than that in the healthy cases 52.3 ± 32.6 degrees ( p < 0.001). Significance. Being non-intrusive and non-subjective, this computer-aided method can be useful in the monitoring for respiratory rate and chest indrawing for the diagnosis of pneumonia and its severity in children.

Synchrotron X-ray radiation (SXR) has been widely studied to explore the structure of matter. Recently, there has been an intense focus on the medical application of SXR in imaging. This review is intended to explore the latest applications of SXR in medical imaging and to shed light on the advantages and drawbacks of this modality. The article highlights the latest developments in other fields that can greatly enhance the capability and applicability of SXR. The potentials of using machine and deep learning (DL)-based methods to generate synthetic images to use in regular clinics along with the use of photon counting X-ray detectors for spectral medical imaging with SXR are also discussed.