Advanced imaging and artificial intelligence for Barrett's esophagus:What we should and soon will do

Barrett’s esophagus(BE)is a well-established risk factor for esophageal adenocarcinoma.It is recommended that patients have regular endoscopic surveillance,with the ultimate goal of detecting early-stage neoplastic lesions before they can progress to invasive carcinoma.Detection of both dysplasia or early adenocarcinoma permits curative endoscopic treatments,and with this aim,thorough endoscopic assessment is crucial and improves outcomes.The burden of missed neoplasia in BE is still far from being negligible,likely due to inappropriate endoscopic surveillance.Over the last two decades,advanced imaging techniques,moving from traditional dye-spray chromoendoscopy to more practical virtual chromoendoscopy technologies,have been introduced with the aim to enhance neoplasia detection in BE.As witnessed in other fields,artificial intelligence(AI)has revolutionized the field of diagnostic endoscopy and is set to cover a pivotal role in BE as well.The aim of this commentary is to comprehensively summarize present evidence,recent research advances,and future perspectives regarding advanced imaging technology and AI in BE;the combination of computer-aided diagnosis to a widespread adoption of advanced imaging technologies is eagerly awaited.It will also provide a useful step-by-step approach for performing high-quality endoscopy in BE,in order to increase the diagnostic yield of endoscopy in clinical practice.

Recent advances in imaging techniques of renal masses

Multiphasic multidetector computed tomography(CT)forms the mainstay for the characterization of renal masses whereas magnetic resonance imaging(MRI)acts as a problem-solving tool in some cases.However,a few of the renal masses remain indeterminate even after evaluation by conventional imaging methods.To overcome the deficiency in current imaging techniques,advanced imaging methods have been devised and are being tested.This review will cover the role of contrast-enhanced ultrasonography,shear wave elastography,dual-energy CT,perfusion CT,MR perfusion,diffusion-weighted MRI,blood oxygen leveldependent MRI,MR spectroscopy,positron emission tomography(PET)/prostate-specific membrane antigen-PET in the characterization of renal masses.

Application of Spectral Angle Mapper Classification to Discriminate Hydrothermal Alteration in Southwest Birjand, Iran, Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Image Processing

The purpose of this study is to evaluate the Spectral Angle Mapper （SAM） classification method for determining the optimum threshold （maximum spectral angle） to unveil the hydrothermal mineral assemblages related to mineral deposits. The study area indicates good potential for Cu-Au porphyry, epithermal gold deposits and hydrothermal alteration well developed in arid and semiarid climates, which makes this region significant for Advanced Spaceborne Thermal Emission and Reflection Radiometer （ASTER） image processing analysis. Given that achieving an acceptable mineral mapping requires knowing the alteration patterns, petrochemistry and petrogenesis of the igneous rocks while considering the effect of weathering, overprinting of supergene alteration, overprinting of hypogene alteration and host rock spectral mixing, SAM classification was implemented for argillic, sericitic, propylitic, alunitization, silicification and iron oxide zones of six previously known mineral deposits： Maherabad, a Cu-Au porphyry system; Sheikhabad, an upper part of Cu-Au porphyry system; Khoonik, an Intrusion related Au system; Barmazid, a low sulfidation epithermal system; Khopik, a Cu-Au porphyry system; and Hanish, an epithermal Au system. Thus, the investigation showed that although the whole alteration zones are affected by mixing, it is also possible to produce a favorable hydrothermal mineral map by such complementary data as petrology, petrochemistry and alteration patterns.

Real-time histology with the endocytoscope

Endoscopic Imaging has progressed tremendously over the last few decades. Novel imaging technologies such as high-resolution and high-magnification white light endoscopy, narrow band imaging, optimal band imaging, auto? ourescence imaging and optical coherence tomography not only aid the endoscopist in detecting malignant or pre-malignant lesions but also assist in predicting histology. Recently, the introduction of Endocytoscopy (EC) and Confocal Endomicroscopy has taken us into a new realm of diagnostic endoscopy. With the ability to magnify up to 1000 ×, cellular structures can be visualized in real-time. This advance in technology could potentially lead to a paradigm shift negating the need to obtain biopsies. EC is, however, still in the early stages of development and further research needs to be carried out before it can be accepted as standard practice. This review will focus on the diagnostic utility of the Endocytoscope.

Comparison of TMI and AMSR-E sea surface temperatures with Argo near-surface temperatures over the global oceans

Satellite-derived sea surface temperatures（SSTs） from the tropical rainfall measuring mission（TRMM）microwave imager（TMI） and the advanced microwave scanning radiometer for the earth observing system（AMSR-E） were compared with non-pumped near-surface temperatures（NSTs） obtained from Argo profiling floats over the global oceans. Factors that might cause temperature differences were examined, including wind speed, columnar water vapor, liquid cloud water, and geographic location. The results show that both TMI and AMSR-E SSTs are highly correlated with the Argo NSTs; however, at low wind speeds, they are on average warmer than the Argo NSTs. The TMI performs slightly better than the AMSR-E at low wind speeds, whereas the TMI SST retrievals might be poorly calibrated at high wind speeds. The temperature differences indicate a warm bias of the TMI/AMSR-E when columnar water vapor is low, which can indicate that neither TMI nor AMSR-E SSTs are well calibrated at high latitudes. The SST in the Kuroshio Extension region has higher variability than in the Kuroshio region. The variability of the temperature difference between the satellite-retrieved SSTs and the Argo NSTs is lower in the Kuroshio Extension during spring. At low wind speeds, neither TMI nor AMSR-E SSTs are well calibrated, although the TMI performs better than the AMSR-E.

“To measure is to know”: how advances in image analysis are supporting neural repair strategies

Neuronal regeneration in the peripheral nervous system arises via a synergistic interplay of neurotrophic factors,integrins,cytoskeletal proteins,mechanical cues,cytokines,stem cells,glial cells and astrocytes.

Synthesis of True Color Images from the Fengyun Advanced Geostationary Radiation Imager

The production of true color images requires observational data in the red,green,and blue(RGB)bands.The Advanced Geostationary Radiation Imager(AGRI)onboard China’s Fengyun-4(FY-4)series of geostationary satellites only has blue and red bands,and we therefore have to synthesize a green band to produce RGB true color images.We used random forest regression and conditional generative adversarial networks to train the green band model using Himawari-8 Advanced Himawari Imager data.The model was then used to simulate the green channel reflectance of the FY-4 AGRI.A single-scattering radiative transfer model was used to eliminate the contribution of Rayleigh scattering from the atmosphere and a logarithmic enhancement was applied to process the true color image.The conditional generative adversarial network model was better than random forest regression for the green band model in terms of statistical significance(e.g.,a higher determination coefficient,peak signal-to-noise ratio,and structural similarity index).The sharpness of the images was significantly improved after applying a correction for Rayleigh scattering,and the images were able to show natural phenomena more vividly.The AGRI true color images could be used to monitor dust storms,forest fires,typhoons,volcanic eruptions,and other natural events.

Advances in the light field displays based on integral imaging and holographic techniques(Invited Paper)

Light field displays comprise three-dimensional （3D） visual information presentation devices capable of providing realistic and full parallax autostereoscopic images. In this letter, the recent advances in the light field displays based on integral imaging （II） and holographic techniques are presented. Several advanced approaches to demonstrate the light field displays including viewing angle enhancement techniques of the II display, a fast hologram generation method using graphics processing unit （GPU） and multiple WRPs, and a holographic microscopy to display the living cells are reported. These methods improve some important constraints of the light field displays and add new features.

Advances in active fire detection using a multi-temporal method for next-generation geostationary satellite data

A vital component of fire detection from remote sensors is the accurateestimation of the background temperature of an area in fire’s absence,assisting in identification and attribution of fire activity. Newgeostationary sensors increase the data available to describebackground temperature in the temporal domain. Broad area methodsto extract the expected diurnal cycle of a pixel using this temporally richdata have shown potential for use in fire detection. This paper describesan application of a method for priming diurnal temperature fitting ofimagery from the Advanced Himawari Imager. The BAT method is usedto provide training data for temperature fitting of target pixels, to whichthresholds are applied to detect thermal anomalies in 4 μm imageryover part of Australia. Results show the method detects positive thermalanomalies with respect to the diurnal model in up to 99% of caseswhere fires are also detected by Low Earth Orbiting (LEO) satellite activefire products. In absence of LEO active fire detection, but where aburned area product recorded fire-induced change, this method alsodetected anomalous activity in up to 75% of cases. Potentialimprovements in detection time of up to 6 h over LEO products are alsodemonstrated.

Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES-16 satellite

Surface upward longwave radiation(SULR)is one of the four components of the surface radiation budget,which is defined as the total surface upward radiative flux in the spectral domain of 4-100μm.The SULR is an indicator of surface thermal conditions and greatly impacts weather,climate,and phenology.Big Earth data derived from satellite remote sensing have been an important tool for studying earth science.The Advanced Baseline Imager(ABI)onboard the Geostationary Operational Environmental Satellite(GOES-16)has greatly improved temporal and spectral resolution compared to the imager sensor of the previous GOES series and is a good data source for the generation of high spatiotemporal resolution SULR.In this study,based on the hybrid SULR estimation method and an upper hemisphere correction method for the SULR dataset,we developed a regional clear-sky land SULR dataset for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020.The dataset was validated against surface measurements collected at 65 Ameriflux radiation network sites.Compared with the SULR dataset of the Global LAnd Surface Satellite(GLASS)longwave radiation product that is generated from the Moderate Resolution Imaging Spectroradiometer(MODIS)onboard the polar-orbiting Terra and Aqua satellites,the ABI/GOES-16 SULR dataset has commensurate accuracy(an RMSE of 15.9 W/m2 vs 19.02 W/m2 and an MBE of−4.4 W/m2 vs−2.57 W/m2),coarser spatial resolution(2 km at nadir vs 1 km resolution),less spatial coverage(most of the Americas vs global),fewer weather conditions(clear-sky vs all-weather conditions)and a greatly improved temporal resolution(48 vs 4 observations a day).The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00062.