Estimation of tissue oxygen saturation from RGB images and sparse hyperspectral signals based on conditional generative adversarial network

Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery

Laparoscopic surgery has evolved as a key technique for cancer diagnosis and therapy. While characterization of the tissue perfusion is crucial in various procedures, such as partial nephrectomy, doing so by means of visual inspection remains highly challenging. We developed a laparoscopic real-time multispectral imaging system featuring a compact and lightweight multispectral camera and the possibility to complement the conventional surgical view of the patient with functional information at a video rate of 25 Hz. To enable contrast agent-free ischemia monitoring during laparoscopic partial nephrectomy, we phrase the problem of ischemia detection as an out-of-distribution detection problem that does not rely on data from any other patient and uses an ensemble of invertible neural networks at its core. An in-human trial demonstrates the feasibility of our approach and highlights the potential of spectral imaging combined with advanced deep learning-based analysis tools for fast, efficient, reliable, and safe functional laparoscopic imaging.

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Covid-19 pandemic and its impact on increasing the risks of children's addiction to electronic games from a social work perspective

Children are among the social groups most affected by the COVID-19 pandemic because they have found themselves forced to stay at home, far from their schoolmates, their friends, and far from all the activities they used to do before the pandemic. so, it was their only refuge for recreation during their stay in Home is staying in front of the screens of tablets, smartphones, and computers to play electronic games for long hours, and there is no doubt that the sudden shift in the lifestyle of children during the Covid-19 pandemic had serious consequences and risks threatening their stability at all levels. In light of that, the current study aimed to determine the impact of the Covid-19 pandemic on increasing the social, psychological, behavioral, and health risks of children's addiction to electronic games from a social work perspective. This study falls under the type of descriptive-analytical studies that are based on describing the reality of the problem under study. The study sample included 289 children in the age group 6-17 years in the first grade to the twelfth grade at school. The researcher designed a questionnaire that reflects the four risks facing children to assess these risks. The results showed is that the value of all impacts of the Covid-19 pandemic on the increasing risks of children's addiction to electronic games came to a total weight of (27907), weighted relative weight of (80.47%). This indication is High, indicating that the level of impact is High for the Covid-19 pandemic on the increase in all types of risks of children's addiction to electronic games. It ranked first " Behavioral Risks " at 91.15%, It is followed by the ranked second "Social risks " at 85.5%, Then came third place " Psychological Risks" at 80.91%, and in finally in fourth place " Health Risks" at 64.28%, which necessitates the need to take a set of serious measures by educating parents to monitor the content of electronic games that their children play, especially violent games, in addition to, reduce the number of hours the child spends practicing these games, and to encourage parents to form a bridge of communication and constructive dialogue between them and their children, and that parents put controls and restrictions on their children's practice of electronic games to confront abnormal behavioral, psychological and social patterns such as aggression, violence, deception, lying, imitation, vigilance, physical stress, poor eyesight, distance from practicing religious rituals, academic delay, introversion, depression, intolerance, selfishness, sadness, isolation from society, social withdrawal and lack of forming social relationships and lack of communication with others. The researcher took care that the results of the current study are very accurate and representative of the reality of the research problem, in light of the researcher's emphasis on the commitment to observe ethical rules to ensure the confidentiality of data. finally, the current study will greatly benefit researchers interested in the field of childhood and its problems and they will rely on its results and recommendations in how to protect children from the dangers of electronic game addiction in light of the Covid-19 crisis in particular.

Surgical spectral imaging

Recent technological developments have resulted in the availability of miniaturised spectral imaging sensors capable of operating in the multi- (MSI) and hyperspectral imaging (HSI) regimes. Simultaneous advances in image-processing techniques and artificial intelligence (AI), especially in machine learning and deep learning, have made these data-rich modalities highly attractive as a means of extracting biological information non-destructively. Surgery in particular is poised to benefit from this, as spectrally-resolved tissue optical properties can offer enhanced contrast as well as diagnostic and guidance information during interventions. This is particularly relevant for procedures where inherent contrast is low under standard white light visualisation. This review summarises recent work in surgical spectral imaging (SSI) techniques, taken from Pubmed, Google Scholar and arXiv searches spanning the period 2013-2019. New hardware, optimised for use in both open and minimally-invasive surgery (MIS), is described, and recent commercial activity is summarised. Computational approaches to extract spectral information from conventional colour images are reviewed, as tip-mounted cameras become more commonplace in MIS. Model-based and machine learning methods of data analysis are discussed in addition to simulation, phantom and clinical validation experiments. A wide variety of surgical pilot studies are reported but it is apparent that further work is needed to quantify the clinical value of MSI/HSI. The current trend toward data-driven analysis emphasises the importance of widely-available, standardised spectral imaging datasets, which will aid understanding of variability across organs and patients, and drive clinical translation.