Near-infrared Camera Research Articles

Domain-Specific Adaptation of CNN for Detecting Face Presentation Attacks in NIR

For the automotive industry moving towards personalized applications and experiences, the identification of the person inside vehicle is necessary; and it must be carried out in a secure manner. In this paper, we propose a unique face presentation attack detection (PAD) system for operation inside a passenger vehicle. A typical <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-vehicular</i> face PAD system is required to function with several constraints such as bounded sensing (imaging) capabilities, limited computing resources on embedded devices, real-time inference, and essentially, very high accuracy. In this work, we develop a face PAD system for automotive domain, relying on a single NIR camera, to continually verify whether the driver’s face is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">bona-fide</i> or not. Our work has two main contributions: first, a lightweight face PAD framework has been developed using a 9-layer convolutional neural network (CNN). With its compact size and limited set of operators, it can be deployed in a resource constrained embedded device to achieve a near real-time inference. To alleviate the problem of limited training data (face PAD in NIR) for a given system, we develop an efficient mechanism to obtain this CNN through the combination of adaptation of domain-specific layers and task-specific fine-tuning of a base CNN. As the second contribution, we collect a large face PAD dataset with 5800+ videos, acquired in NIR (940 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nm</i> ) illumination, for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-vehicular</i> use-cases. This dataset, named VFPAD, captures several real-world variations in terms of environmental settings, illumination, subject’s pose, and appearances. Based on the VFPAD dataset, we demonstrate that the proposed face PAD method achieves very high performance (overall accuracy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 98.0$ </tex-math></inline-formula> %), and also outperforms several baseline face PAD methods. The dataset will be shared with the wider scientific community for research purposes.

Application of indocyanine green fluorescence visualization in surgical resection of abdominal wall endometriosis

Objective: To investigate the feasibility, effectiveness and safety of indocyanine green (ICG) navigation in the surgical resection of abdominal wall endometriosis (AWE). Methods: Seven women undergoing surgery for AWE in First Affiliated Hospital of Sun Yat-sen University (from July 1, 2021 to October 1, 2021) were collected. After exposure of the focus, ICG were used intravenously (0.25 mg/kg) as fluorescent dye for the intraoperative evaluation of AWE vascularization. Resection of the AWE was guided by direct visualization of the focus under standard laparoscopy with a near-infrared (NIR) camera head. Surgical margin around the AWE (3, 6, 9 and 12 point) and the margin under the focus were obtained for postoperative pathological examination of endometriosis. Time from injection to fluorescence visualization, the proportion of fluorescence visualization, time of fully resection of AWE, side effects related to the use of ICG, perioperative complications as well as the pathological result of the surgical margins were recorded. Results: ICG fluorescence of the AWE were seen in 5 patients (5/7). The mean time from injection to fluorescence visualization was (46.7±9.8) s. The mean time of fully resection of AWE was (16.4±7.0) minutes. There were no side effects related to the use of ICG. The rate of class-A wound healing was 7/7. All of the surgical margins were confirmed endometriosis-negative by postoperative pathological examination. Conclusion: ICG fluorescence visualization could conduct accurate resection of AWE, which is clinically safe and effective.

Warping-based spectral translation network for unsupervised cross-spectral stereo matching

Recently, a pair of RGB and near-infrared (NIR) cameras is applied to stereo vision systems for all-day vision applications. The images captured by the RGB-NIR stereo vision system have spectral ranges that differ significantly. Hence, the NIR image displays richer image information during nighttime. By contrast, during daytime, the RGB image generally provides abundant information. Therefore, these images can complement each other’s disadvantages in all-day environments. However, from the perspective of image matching, it is difficult to search for correspondences between two images because of their different spectral ranges. Although various methods for translating RGB images into NIR images have been proposed to solve this problem, hight-quality conversion results have not been achieved. Incomplete conversion results cause the inaccurate estimation of disparity during stereo matching. Therefore, we propose a warping-based spectral translation network (WASTNet) to enhance the training performance of a disparity estimation network by improving the performance of image translation.The WASTNet involves the following three steps: (1) initial disparity estimation for warping an NIR image to the viewpoint of RGB image; (2) post-processing for enhancing the initial disparity map; (3) image warping and spectral translation. Furthermore, we propose a confidence-based smoothness term that is applied to a loss function to mitigate disparity errors in the disparity map. The WASTNet and the proposed smoothness term are used concurrently with a conventional spectral translation network, which improves the performance of an unsupervised stereo matching network.

Webb telescope goes into space

Webb telescope goes into space

Intraoperative Near-Infrared Fluorescence Guided Surgery Using Indocyanine Green (ICG) for the Resection of Sarcomas May Reduce the Positive Margin Rate: An Extended Case Series.

Simple SummarySarcomas are rare cancers that can arise all over the body, with many occurring in younger people. Treatment is usually based around surgery to remove the tumour. It is crucial to remove all of the tumour to minimise the chance of the tumour coming back. Currently, surgeons review scans of the tumour and plan the operation beforehand, but it can be difficult to relate the scans to what the surgeon sees during the operation. Currently, there are no established technologies to help them identify the tumour during the operation. Here we have given patients a harmless dye (indocyanine green) prior to the operation, which makes the tumour glow on a screen when seen by a camera during the operation, helping the surgeon to identify and remove the tumour. This resulted in the surgeon being able to remove all of the tumour more often, reducing the chances of it coming back.Background: Sarcomas are rare, aggressive cancers which can occur in any region of the body. Surgery is usually the cornerstone of curative treatment, with negative surgical margins associated with decreased local recurrence and improved overall survival. Indocyanine green (ICG) is a fluorescent dye which accumulates in sarcoma tissue and can be imaged intraoperatively using handheld near-infrared (NIR) cameras, theoretically helping guide the surgeon’s resection margins. Methods: Patients operated on between 20 February 2019 and 20 October 2021 for intermediate to high grade sarcomas at our centres received either conventional surgery, or were administered ICG pre-operatively followed by intra-operative NIR fluorescence guidance during the procedure. Differences between the unexpected positive margin rates were compared. Results: 115 suitable patients were identified, of which 39 received ICG + NIR fluorescence guided surgery, and 76 received conventional surgery. Of the patients given ICG, 37/39 tumours fluoresced, and surgeons felt the procedure was guided by the intra-operative images in 11 cases. Patients receiving ICG had a lower unexpected positive margin rate (5.1% vs. 25.0%, p = 0.01). Conclusions: The use of NIR fluorescence cameras in combination with ICG may reduce the unexpected positive margin rate for high grade sarcomas. A prospective, multi-centre randomised control trial is now needed to validate these results.

Indocyanine Green to Assess Vascularity of Ileal Conduit Anastomosis During Pelvic Exenteration for Recurrent/Persistent Gynecological Cancer: A Pilot Study.

IntroductionPelvic exenteration performed for recurrent/persistent gynecological malignancies has been associated with urological short- and long-term morbidity due to altered vascularization of tissues for previous radiotherapy. The aims of the present study were to describe the use of intravenous indocyanine green (ICG) to assess vascularity of urinary diversion (UD) after pelvic exenteration for gynecologic cancers, to evaluate the feasibility and safety of this technique, and to assess the postoperative complications.MethodsProspective, observational, single-center, pilot study including consecutive patients undergoing anterior or total pelvic exenteration due to persistent/recurrent gynecologic cancers between August 2020 and March 2021 at Fondazione Policlinico Gemelli IRCCS, Rome, Italy. All patients underwent intravenous injection of 3–6 ml of ICG (1.25 mg/ml) once the UD was completed. A near-infrared camera was used to evaluate ICG perfusion of anastomoses (ileum–ileum, right and left ureter with small bowel, and colostomy or colorectal sides of anastomosis) a few seconds after ICG injection.ResultsFifteen patients were included in the study. No patient reported adverse reactions to ICG injection. Only 3/15 patients (20.0%) had an optimal ICG perfusion in all anastomoses. The remaining 12 (80.0%) patients had at least one ICG deficit; the most common ICG deficit was on the left ureter: 3 (20.0%) vs. 1 (6.7%) patient had no ICG perfusion on the left vs. right ureter, respectively (p = 0.598). 8/15 (53.3%) and 6/15 (40.0%) patients experienced grade ≥3 30-day early and late postoperative complications, respectively. Of these, two patients had early and one had late postoperative complications directly related to poor perfusion of anastomosis (UD leak, ileum–ileum leak, and benign ureteric stricture); all these cases had a suboptimal intraoperative ICG perfusion.ConclusionThe use of ICG to intraoperatively assess the anastomosis perfusion at time of pelvic exenteration for gynecologic malignancy is a feasible and safe technique. The different vascularization of anastomotic stumps may be related to anatomical sites and to previous radiation treatment. This approach could be in support of selecting patients at higher risk of complications who may need personalized follow-up.

Bat point counts: A novel sampling method shines light on flying bat communities.

Emerging technologies based on the detection of electro‐magnetic energy offer promising opportunities for sampling biodiversity. We exploit their potential by showing here how they can be used in bat point counts—a novel method to sample flying bats—to overcome shortcomings of traditional sampling methods, and to maximize sampling coverage and taxonomic resolution of this elusive taxon with minimal sampling bias. We conducted bat point counts with a sampling rig combining a thermal scope to detect bats, an ultrasound recorder to obtain echolocation calls, and a near‐infrared camera to capture bat morphology. We identified bats with a dedicated identification key combining acoustic and morphological features, and compared bat point counts with the standard bat sampling methods of mist‐netting and automated ultrasound recording in three oil palm plantation sites in Indonesia, over nine survey nights. Based on rarefaction and extrapolation sampling curves, bat point counts were similarly effective but more time‐efficient than the established methods for sampling the oil palm species pool in our study. Point counts sampled species that tend to avoid nets and those that are not echolocating, and thus cannot be detected acoustically. We identified some bat sonotypes with near‐infrared imagery, and bat point counts revealed strong sampling biases in previous studies using capture‐based methods, suggesting similar biases in other regions might exist. Our method should be tested in a wider range of habitats and regions to assess its performance. However, while capture‐based methods allow to identify bats with absolute and internal morphometry, and unattended ultrasound recorders can effectively sample echolocating bats, bat point counts are a promising, non‐invasive, and potentially competitive new tool for sampling all flying bats without bias and observing their behavior in the wild.

Dual Image-Based CNN Ensemble Model for Waste Classification in Reverse Vending Machine

A reverse vending machine motivates citizens to bring recyclable waste by rewarding them, which is a viable solution to increase the recycling rate. Reverse vending machines generally use near-infrared sensors, barcode sensors, or cameras to classify recycling resources. However, sensor-based reverse vending machines suffer from a high configuration cost and the limited scope of target objects, and conventional single image-based reverse vending machines usually make erroneous predictions about intentional fraud objects. This paper proposes a dual image-based convolutional neural network ensemble model to address these problems. For this purpose, we first created a prototype reverse vending machine and constructed an image dataset containing two cross-sections of objects, top and front view. Then, we chose convolutional neural network models widely used in image classification as the candidates for building an accurate and lightweight ensemble model. Considering the size and classification performance of candidates, we constructed the best-fit ensemble combination and evaluated its classification performance. The final ensemble model showed a classification accuracy higher than 95% for all target classes, including fraud objects. This result proves that our approach achieves better robustness against intentional fraud objects than single image-based models and thus can broaden the scope for target resources. The measurement results on lightweight embedded platforms also demonstrated that our model provides a short inference time that is enough to facilitate the real-time execution of reverse vending machines based on low-cost edge artificial intelligence devices.

Synthetic aperture metalens

Metalenses are ultrathin optical elements that can focus light using densely arranged subwavelength structures. Due to their minimal form factor, they have been considered promising for imaging applications that require extreme system size, weight, and power, such as in consumer electronics and remote sensing. However, as a major impediment prohibiting the wide adoption of the metalens technology, the aperture size, and consequently the imaging resolution, of a metalens are often limited by lithography processes that are not scalable. Here, we propose to adopt a synthetic aperture approach to alleviate the issue, and experimentally demonstrate that, assisted by computational reconstruction, a synthetic aperture metalens composed of multiple metalenses with relatively small aperture size can achieve an imaging resolution comparable to a conventional lens with an equivalent large aperture. We validate the concept via an outdoor imaging experiment performed with a synthetic aperture metalens-integrated near-infrared camera using natural sunlight for target illumination.

Water and nitrogen in-situ imaging detection in live corn leaves using near-infrared camera and interference filter

BackgroundRealizing imaging detection of water and nitrogen content in different regions of plant leaves in-site and real-time can provide an efficient new technology for determining crop drought resistance and nutrient regulation mechanisms, or for use in precision agriculture. Near-infrared imaging is the preferred technology for in-situ real-time detection owing to its non-destructive nature; moreover, it provides rich information. However, the use of hyperspectral imaging technology is limited as it is difficult to use it in field because of its high weight and power.ResultsWe developed a smart imaging device using a near-infrared camera and an interference filter; it has a low weight, requires low power, and has a multi-wavelength resolution. The characteristic wavelengths of the filter that realize leaf moisture measurement are 1150 and 1400 nm, respectively, the characteristic wavelength of the filter that realizes nitrogen measurement is 1500 nm, and all filter bandwidths are 25 nm. The prediction result of the average leaf water content model obtained with the device was R2 = 0.930, RMSE = 1.030%; the prediction result of the average nitrogen content model was R2 = 0.750, RMSE = 0.263 g.ConclusionsUsing the average water and nitrogen content model, an image of distribution of water and nitrogen in different areas of corn leaf was obtained, and its distribution characteristics were consistent with the actual leaf conditions. The experimental materials used in this research were fresh leaves in the field, and the test was completed indoors. Further verification of applying the device and model to the field is underway.

The feasibility of using a low-cost near-infrared, sensitive, consumer-grade digital camera mounted on a commercial UAV to assess Bambara groundnut yield

ABSTRACT Accurate, timely, and non-destructive early crop yield prediction at the field scale is essential in addressing changing crop production challenges and mitigating impacts of climate variability. Unmanned aerial vehicles (UAVs) are increasingly popular in recent years for agricultural remote sensing applications such as crop yield forecasting and precision agriculture (PA). The objective of this study was to evaluate the performance of a low-cost UAV-based remote sensing technology for Bambara groundnut yield prediction. A multirotor UAV equipped with a near-infrared sensitive consumer-grade digital camera was used to collect image data during the 2018 growing season (April to August). Flight missions were carried out six times during critical phenological stages of the life-cycle of the monitored crop. Yield was recorded at harvest. Four vegetation indices (VIs) namely normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), green normalized difference vegetation index (GNDVI), and simple ratio (SR) generated from the Red-Green-Near Infrared bands were calculated using the georeferenced orthomosaic UAV images. Pearson’s product-moment correlation coefficient (r) and Bland–Altman testing showed a significant agreement between remotely and proximally sensed VIs. Significant and positive correlations were found between the four VIs and yield, with the strongest relationship observed between SR and yield at podfilling stage (r = 0.81, P < 0.01). Multi-temporal accumulative VIs improved yield prediction significantly with the best index being ∑SR and the best interval being from podfilling to maturity (r = 0.88, P < 0.01). The accumulated ∑SR from podfilling to maturity resulted in higher prediction accuracy with a coefficient of determination (R 2) of 0.71, root mean square error (RMSE) of 0.20 and mean absolute percentage error (MAPE) of 14.2% than SR spectral index at a single stage (R 2 = 0.68, RMSE = 0.24, MAPE = 15.1%). Finally, a yield map was generated using the model developed, to better understand the within-field spatial variations of yield for future site-specific or variable-rate application operations.

Improved intraoperative verification of parathyroid glands by determining their autofluorescence in the infrared spectrum

Background. Detection of parathyroid glands by spectroscopy of their autofluorescence in the near-infrared spectrum (NIRAF) is considered a promising intraoperative tool in addition to their verification with visual identification. The study was aimed to evaluate the role of NIRAF by using two different imaging systems to confirm parathyroid glands during operations for benign and malignant thyroid and parathyroid tumors. Materials and methods. The study included 62 patients who underwent verification of NIRAF by using two different imaging systems equipped with a near-infrared (NIR) camera during surgery. Intravenous fluorophore of indocyanine green was applied to amplify the NIRAF signal. Results. Normal parathyroid glands were identified and mobilized after a visual inspection in 50 patients (80 %), which was subsequently confirmed by evaluation with NIRAF spectroscopy. Determination of NIRAF in the parathyroid glands and their differentiation from lymph nodes was achieved in 8 (13 %) patients with papillary thyroid carcinoma. In 3 (5 %) patients, the parathyroid gland was identified in the area of the postoperative scar, using NIRAF but not by the visual identification. In 2 (3 %) cases, the appearance of the signal was determined but with a decrease in the intensity of the NIRAF from the parathyroid glands during their unintentional removal. The strong NIRAF signal intensity was observed from the parathyroid gland after changing the position of the NIR camera when using the Fluobeam 800 device at an angle of approximately 45–65° to the area of the parathyroid gland location. The Fluobeam LX demonstrated a satisfactory NIRAF signal without any specific changes in camera position. NIRAF signal was determined in the tissue of toxic thyroid adenomas. NIRAF signal of the low intensity was detected in the invasion of thyroid carcinoma in a capsule of a thyroid gland. No NIRAF signal was observed from metastatic and normal lymph nodes. Conclusions. The use of NIRAF parathyroid spectroscopy technology allows impro-ving their imaging and verification as an additional method during surgery of the neck. The practical value of NIRAF spectroscopy of the parathyroid gland is increased in the case of reoperations due to the risk of accidental removal of the parathyroid gland as well as for differential diagnosis between the parathyroid gland and metastatic lymph nodes.

The NEWFIRM HETDEX Survey: Photometric Catalog and a Conservative Sample of Massive Quiescent Galaxies at z = 3–5 over 17.5 deg2 in the SHELA Field

Abstract We present the results of a deep K s -band (2.1 μm) imaging survey of the Spitzer/HETDEX Exploratory Large-Area (SHELA) field using the NEWFIRM near-infrared camera on the KPNO Mayall 4 m telescope. This NEWFIRM HETDEX Survey reaches a 5σ depth of 22.4 AB mag (2″-diameter apertures corrected to total), is ∼50% and 90% complete at K ∼ 22.65 and K ∼ 22.15, respectively, and covers 22 deg2 of the 24 deg2 SHELA Spitzer/IRAC footprint (within “Stripe 82” of the Sloan Digital Sky Survey). We present a K s -band-selected catalog that includes deep ugriz imaging from the Dark Energy Camera and 3.6 and 4.5 μm imaging from Spitzer/IRAC, with forced photometry of 1.7 million sources across 17.5 deg2. The large area and moderate depth of this catalog enable the study of the most massive galaxies at high redshift and minimize uncertainties associated with counting statistics and cosmic variance. As a demonstration, we derive stellar masses (M *) and star formation rates (SFRs) for candidate galaxies at 3 ≲ z ≲ 5 and select a conservative sample of nine candidate massive (M * &gt; 1011 M ⊙) quiescent galaxies, which have measured SFRs significantly below the main sequence at this redshift. Five are ultramassive with M * &gt; 1012, though uncertainties in IRAC blending, gravitational lensing, or active galactic nucleus emission could result in true masses that are lower. Simulations predict that these galaxies should be extremely rare; thus, we conclude by discussing what physical processes in models could be altered to allow the formation of such massive quiescent galaxies at such early times.

MTCD: Cataract detection via near infrared eye images

Globally, cataract is a common eye disease and one of the leading causes of blindness and vision impairment. The traditional process of detecting cataracts involves eye examination using a slit-lamp microscope or ophthalmoscope by an ophthalmologist, who checks for clouding of the normally clear lens of the eye. The lack of resources and unavailability of a sufficient number of experts pose a burden to the healthcare system throughout the world, and researchers are exploring the use of AI solutions for assisting the experts. Inspired by the progress in iris recognition, in this research, we present a novel algorithm for cataract detection using near-infrared eye images. The NIR cameras, which are popularly used in iris recognition, are of relatively low cost and easy to operate compared to ophthalmoscope setup for data capture. However, such NIR images have not been explored for cataract detection. We present deep learning-based eye segmentation and multitask network classification networks for cataract detection using NIR images as input. The proposed segmentation algorithm efficiently and effectively detects non-ideal eye boundaries and is cost-effective, and the classification network yields very high classification performance on the cataract dataset.

Laparoscopic cholecystectomy completely guided by indocyanine green fluorescence in a patient with gallstone: A case report.

IntroductionWe report the execution of a cholecystectomy under complete fluorescence guidance using near-infrared camera images without switching to the white light mode, a method that has not been reported previously.Presentation of caseAn Asian woman in her fifties with no history of abdominal surgery was administered indocyanine green (ICG, 25 mg) intravenously 16 h before the surgery. Laparoscopic surgery was performed using VISION SENSE® with the four-trocar technique. The entire laparoscopic procedure was performed under fluorescence guidance. The orientation of the gallbladder neck can be recognized from the beginning of the procedure, and the serosal first incision could be positioned appropriately. All procedures were performed while the common bile duct was visualized. Peeling around the cystic duct and gallbladder bed was appropriately guided by ICG fluorescence.DiscussionThis method may be a safer form of surgery because the fluorescence did not disturb the surgical procedures.ConclusionSince this method was successful in this case, a case series is warranted.

Doxorubicin-Sensitized Luminescence of NIR-Emitting Ytterbium Liposomes: Towards Direct Monitoring of Drug Release.

Drug-loaded liposomes are typical examples of nanomedicines. We show here that doxorubicin, the anti-cancer agent in the liposomal drug Doxil, can sensitize Ytterbium (Yb3+ ) and generate its near-infrared (NIR) emission. When doxorubicin and amphiphilic Yb3+ chelates are incorporated into liposomes, the sensitized emission of Yb3+ is dependent on the integrity of the particles, which can be used to monitor drug release. We also established the first demonstration that the NIR Yb3+ emission signal is observable in living mice following intratumoral injection of the Yb3+ -doxorubicin-liposomes, using a commercial macroscopic setup equipped with a NIR camera.

Doxorubicin‐Sensitized Luminescence of NIR‐Emitting Ytterbium Liposomes: Towards Direct Monitoring of Drug Release

AbstractDrug‐loaded liposomes are typical examples of nanomedicines. We show here that doxorubicin, the anti‐cancer agent in the liposomal drug Doxil, can sensitize Ytterbium (Yb3+) and generate its near‐infrared (NIR) emission. When doxorubicin and amphiphilic Yb3+ chelates are incorporated into liposomes, the sensitized emission of Yb3+ is dependent on the integrity of the particles, which can be used to monitor drug release. We also established the first demonstration that the NIR Yb3+ emission signal is observable in living mice following intratumoral injection of the Yb3+‐doxorubicin‐liposomes, using a commercial macroscopic setup equipped with a NIR camera.

469 ASSESSMENT OF PERFUSION OF GASTRIC CONDUIT AND PROXIMAL ESOPHAGEAL STUMP BY INDOCYANINE GREEN FLUORESCENCE IMAGING IN PATIENTS UNDERGOING ESOPHAGECTOMY

Abstract Post esophagectomy anastomotic leakage and stricture are crucial factors in determining morbidity and mortality. Good vascularity of the gastric conduit is essential to avoid this complications. This prospective study assesses the utility of intraoperative indocyanine green (ICG) fluorescence imaging to determine gastric conduit vascularity in patients undergoing esophagectomy. Methods Thirteen consecutive patients who were undergoing esophagectomy for carcinoma middle, lower third esophagus or gastro-esophageal junction from August 2019 to September 2019, were included. Three patients underwent laparoscopic-assisted transhiatal esophagectomy, ten thoraco-laparoscopic assisted esophagectomy. Reconstruction was done by gastric pull up via posterior mediastinal route. Vascularity of gastric conduit was assessed by the near-infrared camera using ICG. Results On visual assessment of perfusion at the tip of gastric conduit, it was dusky in 11 patients, pink in two. Fuorescence imaging showed inadequate perfusion at the tip of conduit in 12 patients, needing revision. In one patient visual inspection showed adequate perfusion, but ICG disclosed poor vascularity requiring revision of the conduit’s tip. Resection of the devitalized portion of the proximal esophageal stump was needed in 5 patients both by visual and ICG assessment. The median time to appearance of blush from the time of injection of dye was 15 seconds (10 to 23 seconds). Conclusion Visual inspection of the gastric conduit vascularity can underestimate perfusion and hence can compromise resection of the devitalized part. ICG fluorescence imaging is more objective and promising means to ascertain the vascularity of gastric conduit during an esophagectomy. It could complement the visual inspection to decide the site of anastomosis.

Thermal Imaging Metrology Using High Dynamic Range Near-Infrared Photovoltaic-Mode Camera.

The measurement of a wide temperature range in a scene requires hardware capable of high dynamic range imaging. We describe a novel near-infrared thermal imaging system operating at a wavelength of 940 nm based on a commercial photovoltaic mode high dynamic range camera and analyse its measurement uncertainty. The system is capable of measuring over an unprecedently wide temperature range; however, this comes at the cost of a reduced temperature resolution and increased uncertainty compared to a conventional CMOS camera operating in photodetective mode. Despite this, the photovoltaic mode thermal camera has an acceptable level of uncertainty for most thermal imaging applications with an NETD of 4–12 °C and a combined measurement uncertainty of approximately 1% K if a low pixel clock is used. We discuss the various sources of uncertainty and how they might be minimised to further improve the performance of the thermal camera. The thermal camera is a good choice for imaging low frame rate applications that have a wide inter-scene temperature range.

High-throughput phenotyping to detect anthocyanins, chlorophylls, and carotenoids in red lettuce germplasm

Some plant pigments are strong antioxidants and benefit human health. Given their low cost and popularity, biofortified lettuce cultivars can promote consumption of these compounds. In this study, we assessed anthocyanin, chlorophyll, and carotenoid content in 30 red lettuce genotypes, as well as the Soil Plant Analysis Development index (SPAD) and vegetation indices (CIG, CVI, GNDVI, and NDVI), using high-throughput phenotyping. We calculated vegetation indices by using images of the plant canopy obtained from a remotely piloted aircraft (RPA) together with a red, green, and near-infrared band camera. The SPAD index and leaf pigments were measured through traditional laboratory methods, which are costly and time-consuming. Genetic variability among the genotypes for leaf pigments was confirmed by the Scott-Knott test and UPGMA dendrogram. Anthocyanin was the pigment that most contributed to genetic diversity and highly correlated with CIG, CVI, and GNDVI. These indices also moderately correlated with chlorophylls and carotenoids. Genotypes with higher pigment content, especially anthocyanin, had higher indices. Therefore, the image-based plant phenotyping technique correlated with the traditional methodology and can provide an alternative for indirect selection of plants with high leaf pigment content, especially anthocyanin, in red lettuce.