Efficient Imaging Technique Research Articles

Identifying Crop Distress and Stress-Induced Plant Diseases Using Hyper Spectral Image Analysis

The purpose of this study is to determine whether hyper spectral images can be used to identify plant diseases and crop pressure from aerial photographs. With extensive research on the prevalent methods used closer to the problem, this study offers a potent strategy for identifying crop distress and illnesses using this efficient imaging technique. To identify the spectral fingerprints of common indications and symptoms of plant diseases and crop strains, this study evaluates the available hyper spectral photo datasets. After that, the data are examined using two learning algorithms—the highly randomized trees and the Random Woodland set of rules—to create predictions that are entirely dependent on the results that are discovered. In the end, a benchmarked set of test statistics is used to assess the prediction accuracy. The results of this study show that hyper spectral photo evaluation has a strong and promising utility for crop stress and disease identification. Hyper spectral light evaluation is a method for identifying plant diseases caused by strain on crops. By gathering and evaluating high-dimensional spectral reflection data from satellite or aircraft structures, details regarding the physiological homes of flowers can be identified. The health of plants, illnesses brought on by stress, and agricultural productivity predictions can all be made using these facts. Hyper spectral recordings can also be used to create actions that reduce agricultural losses and enhance the health of plants that are prone to disease.

Spin-lock based fast whole-brain 3D macromolecular proton fraction mapping of relapsing–remitting multiple sclerosis

A sensitive and efficient imaging technique is required to assess the subtle abnormalities occurring in the normal-appearing white matter (NAWM) and normal-appearing grey matter (NAGM) in patients with relapsing–remitting multiple sclerosis (RRMS). In this study, a fast 3D macromolecular proton fraction (MPF) quantification based on spin-lock (fast MPF-SL) sequence was proposed for brain MPF mapping. Thirty-four participants, including 17 healthy controls and 17 RRMS patients were prospectively recruited. We conducted group comparison and correlation between conventional MPF-SL, fast MPF-SL, and DWI, and compared differences in quantified parameters within MS lesions and the regional NAWM, NAGM, and normal-appearing deep grey matter (NADGN). MPF of MS lesions was significantly reduced (7.17% ± 1.15%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} < 0.01) compared to all corresponding normal-appearing regions. MS patients also showed significantly reduced mean MPF values compared with controls in NAGM (4.87% ± 0.38% vs 5.21% ± 0.32%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.01), NAWM (9.49% ± 0.69% vs 10.32% ± 0.59%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} < 0.01) and NADGM (thalamus 5.59% ± 0.67% vs 6.00% ± 0.41%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.04; caudate 5.10% ± 0.55% vs 5.53% ± 0.58%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.03). MPF and ADC showed abnormalities in otherwise normal appearing close to lesion areas (P < 0.01). In conclusion, time-efficient MPF mapping of the whole brain can be acquired efficiently (< 3 min) using fast MPF-SL. It offers a promising alternative way to detect white matter abnormalities in MS.

Dual heterogeneous interfaces enhance X-ray excited persistent luminescence for low-dose 3D imaging

Lanthanide-doped fluoride nanoparticles (NPs) showcase adjustable X-ray-excited persistent luminescence (XEPL), holding significant promise for applications in three-dimensional (3D) imaging through the creation of flexible X-ray detectors. However, a dangerous high X-ray irradiation dose rate and complicated heating procedure are required to generate efficient XEPL for high-resolution 3D imaging, which is attributed to a lack of strategies to significantly enhance the XEPL intensity. Here we report that the XEPL intensity of a series of lanthanide activators (Dy, Pr, Er, Tm, Gd, Tb) is greatly improved by constructing dual heterogeneous interfaces in a double-shell nanostructure. Mechanistic studies indicate that the employed core@shell@shell structure could not only passivate the surface quenchers to lower the non-radiative relaxation possibility, but also reduce the interfacial Frenkel defect formation energy leading to increase the trap concentration. By employing a NPs containing flexible film as the scintillation screen, the inside 3D electrical structure of a watch was clearly achieved based on the delayed XEPL imaging and 3D reconstruction procedure. We foresee that these findings will promote the development of advanced X-ray activated persistent fluoride NPs and offer opportunities for safer and more efficient X-ray imaging techniques in a number of scientific and practical areas.

Prevalence of Knee Pain Pathologies Diagnosed By Musculoskeletal Ultrasound In Nepal Police Hospital

Introduction: One of the most frequent cause of orthopedic consultancy in Nepal Police Hospital is acute and chronic knee pain. The purpose of this study was to demonstrate how musculoskeletal ultrasonography aids in the low-cost identification of knee diseases and using ultrasound to compare with the contra lateral knee can be quite beneficial when developing a treatment plan.&#x0D; Methods: A cross sectional study was conducted on 260 patients with clinically confirmed knee pain. All patients were examined by using Sonasite ultrasound machine with linear probe (7-11MHz). The ultrasound examination of the knee started with examination of anterior aspect, followed by medial aspect, lateral aspect in supine position and then in prone position for examination of posterior aspects. The data were collected, tabulated and statistically analyzed using SPSS11.1. Categorical variables were presented in number and percentage, and continuous variables were presented as mean ± SD.&#x0D; Results: In our study, among the 260 cases there were 164 male patients (63.07%) and 96 females (36.93%) with their age ranged between 25-55 years with the mean age of 40 years. Among 260 cases, 103 patients (39.61%) with knee pain had normal finding and 157 patients (60.39%) had knee pathologies. We found joint effusion (8.91%), quadriceps tendinopathy (3.82%), patellar tendinopathy (1.91%), medial meniscal tear (11.46%), lateral meniscal tear (4.45%), synovial hyperplasia (5.73%), medial collateral ligament tear (10.82%), lateral collateral ligament tear (7%), baker,s cyst(2.54%) and osteophytes(43.31%).&#x0D; Conclusions: An efficient imaging technique that may be used as a screening tool for individuals experiencing knee pain is musculoskeletal ultrasound.

Systematic Exploration Using Intelligent Computing Techniques for Clinical Diagnosis of Gastrointestinal Disorder: A Review

In today's era, the growing ratio of Gastrointestinal (GI) diseases in human beings has become a crucial point of notice and must be diagnosed as early as possible. There are various methods to diagnose abdomen-related problems using medical imaging techniques like ultrasound, endoscopy, Colonoscopy, abdominal CT scan and digital X-ray, etc. Endoscopy is one of the most efficient medical imaging techniques for diagnosing gastrointestinal (GI) diseases. Manual diagnosis of endoscopic images may have a possibility of committing mistakes in properly detecting gastrointestinal disorders because tiny particles are involved in endoscopic images and may be responsible for critical disorders. However, manual diagnosis may ignore such information because of less efficiency of vision and observation. To avoid such problems, various models based on soft computing and neuro-fuzzy techniques have been proposed to detect and classify various gastrointestinal disorders. In this article, the authors propose a systematic review of previous research that has been carried out using intelligent computing methods. Here, various conventional approaches are discussed and compared. This review research shows performance limitations due to complex data models, heterogeneous datasets and the absence of intelligent feature selection methods in diagnosing gastrointestinal disorders.

Application and development of Deuterium Metabolic Imaging in tumor glucose metabolism: visualization of different metabolic pathways

Cancer metabolism has emerged as a pivotal area of research recently. The ability to visualize and comprehend the metabolic processes of cancer holds immense clinical value, particularly in the diagnosis of malignant tumors and the assessment of treatment responses. Deuterium Metabolic Imaging (DMI), as a robust, simple, and versatile MR spectroscopic imaging tool, demonstrates promise in tumor diagnosis and treatment efficacy assessment. This review explored the latest developments and applications of DMI in oncology across various tumor metabolic axes, with a specific emphasis on its potential for clinical translation. DMI offers invaluable insights into tumor biology, treatment responses, and prognostic outcomes. Notably, DMI can identify early responses to immunotherapy, a prominent area of current research interest. In conclusion, DMI harbors the potential to evolve into a convenient and efficient imaging technique in clinical practice, thereby advancing precision medicine and improving the diagnosis and evaluation of cancer treatments.

Efficient and noise-resistant single-pixel imaging based on Pseudo-Zernike moments.

An efficient and noise-resistant single-pixel imaging (SPI) technique based on Pseudo-Zernike moments (PZ-SPI) is proposed. In this technique, the illumination light fields are modulated to satisfy the Pseudo-Zernike polynomials. Then the modulated light fields are projected onto the object. And the single-pixel detector is used to measure the reflected light intensities to calculate the Pseudo-Zernike moments. Finally, the object image is reconstructed by iterative summation of the product of the Pseudo-Zernike polynomials and the Pseudo-Zernike moments. Through the numerical simulation and experimental demonstration, PZ-SPI can effectively reconstruct image at low sampling ratios. Besides, comparing with the Fourier-SPI and Zernike-SPI, PZ-SPI has good robustness to background noise in SPI system. These advantages expand the application of PZ-SPI in complex environments.

Physical and dynamic characteristics of high-amplitude ultrasonic wave propagation in nonlinear and dissipative media

This study presents a comprehensive investigation into the soliton solutions for the Khokhlov–Zabolotskaya–Kuznetsov ([Formula: see text]) problem using the Bernoulli sub-equation function approach, generalized Kudryashov method, and Homotopy perturbation method. The [Formula: see text] equation, a nonlinear wave equation that governs the propagation of high-amplitude ultrasonic waves through nonlinear media, is studied in detail. Perturbation theory and asymptotic expansions are employed to derive approximate solutions for the [Formula: see text] problem. These methodologies offer valuable insights into the behavior of ultrasonic waves in different media, thereby facilitating the optimization of ultrasonic transducer design and enhancing the precision of ultrasonic imaging systems. The analytical and semi-analytical methods utilized for solving the [Formula: see text] equation are computationally efficient and serve as valuable resources for researchers and engineers working in the field of ultrasonics. The outcomes of this study carry significant implications for the understanding of ultrasonic wave behavior in nonlinear and dissipative media, ultimately contributing to the development of more accurate and efficient ultrasonic imaging techniques.

Abstract P1-05-25: Clinical and biological features of 158 consecutive and unselected oligometastatic breast cancers

Abstract Background: In order to determine the optimal treatment strategy for oligometastatic breast cancer (OMBC), effective and safe treatments for metastatic sites and sensitive and specific imaging techniques are needed. But it is also essential to know the incidence of oligometastatic breast cancer and its clinical and biological characteristics [1]. Efficient imaging techniques and therapeutic tools exist, but knowledge of incidence, clinical and biological characteristics of OMBC is scarce. This is partly due to the lack of publications describing these data on recent, consecutive, and unselected series of OMBC. Methods: we retrospectively collected data from 998 patients diagnosed with synchronous or metachronous metastatic breast cancer (MBC) between January 2014 and December 2018 at our institution. The only criterion used to define OMBC was the presence of one to five metastases at diagnosis. Hormone receptor (HR) and HER2 receptor status, histology, SBR grade, number of metastases and organs affected were collected. Results: Of 998 MBC, 15.8% were OMBC (158/998). Among the series, 88% (139/158) of OMBC had 1 to 3 metastases and 86.7% (137/158) had only one organ involved. Among 158 patients, 52.5% (n=83) had bone metastases, 20.9% (n=33) had lymph node metastases, 14.6% (n=23) had liver metastases, 13.3% (n=21) had brain metastases, 8.2% (n=13) had lung metastases, and 3.8% (n=6) had others (skin, pancreas, adrenal). Among these 158 patients, 83.4% (n=131) had ductal breast carcinoma, 55.7% (n=88) had HR+/HER2- OMBC, 25.3% (n=40) had HER2+ OMBC and 19% (n=30) had HR-/HER2- OMBC. HR+/HER2- subtype was statistically associated with bone and bone only metastases (p=0.001), HER2+ subtype with brain metastases (p=0.001) and HR-/HER2- subtype with lymph node metastases (p=0.008). Visceral metastases (lung or liver) are not statistically associated with any biological subtypes. The proportion of OMBC with SBR grade III was statistically higher than in a series of 22,109 patients with MBC [2] (49.4% vs 35.2%; p&amp;lt; 0.001). Conclusion: OMBC is a heterogeneous entity. OMBC incidence is certainly much higher than the commonly used values. OMBC is not an indolent disease, and each subgroup, according to its biological and anatomical characteristics, may deserve a specific management. [1] Hellman S, Weichselbaum RR. Oligometastases. J Clin Oncol Off J Am Soc Clin Oncol 1995;13:8–10. https://doi.org/10.1200/JCO.1995.13.1.8. [2] Deluche E, Antoine A, Bachelot T, Lardy-Cleaud A, Dieras V, Brain E, et al. Contemporary outcomes of metastatic breast cancer among 22,000 women from the multicentre ESME cohort 2008–2016. Eur J Cancer 2020;129:60–70. https://doi.org/10.1016/j.ejca.2020.01.016. Citation Format: Jean Louis LACAZE, Clémence Brac de la Perrière, Mony Ung, Florence Dalenc, Vincent Nicolai, Eleonore De Maio, Marion Montastruc, Bastien Cabarrou, Nils Monselet, Ciprian Chira, Gauthier Glemarec, Thibaut Cassou-Mounat. Clinical and biological features of 158 consecutive and unselected oligometastatic breast cancers [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-05-25.

Image-Guided Optical Coherence Tomography to Assess Structural Changes in Rodent Retinas.

Ocular diseases, such as age-related macular degeneration, glaucoma, retinitis pigmentosa, and uveitis, are always accompanied by retinal structural changes. These diseases affecting the fundus always exhibit typical abnormalities in certain cell types in the retina, including photoreceptor cells, retinal ganglion cells, cells in the retinal blood vessels, and cells in the choroidal vascular cells. Noninvasive, highly efficient, and adaptable imaging techniques are required for both clinical practice and basic research. Image-guided optical coherence tomography (OCT) satisfies these requirements because it combines fundus photography and high-resolution OCT, providing an accurate diagnosis of tiny lesions as well as important changes in the retinal architecture. This study details the procedures of data collection and data analysis for image-guided OCT and demonstrates its application in rodent models of choroidal neovascularization (CNV), optic nerve crush (ONC), light-induced retinal degeneration, and experimental autoimmune uveitis (EAU). This technique helps researchers in the eye field to identify rodent retinal structural changes conveniently, reliably, and tractably.

Three-dimensional imaging and analysis of pathological tissue samples with de novo generation of citrate-based fluorophores.

Two-dimensional (2D) histopathology based on the observation of thin tissue slides is the current paradigm in diagnosis and prognosis. However, labeling strategies in conventional histopathology are limited in compatibility with 3D imaging combined with tissue clearing techniques. Here, we present a rapid and efficient volumetric imaging technique of pathological tissues called 3D tissue imaging through de novo formation of fluorophores, or 3DNFC, which is the integration of citrate-based fluorogenic reaction DNFC and tissue clearing techniques. 3DNFC markedly increases the fluorescence intensity of tissues by generating fluorophores on nonfluorescent amino-terminal cysteine and visualizes the 3D structure of the tissues to provide their anatomical morphology and volumetric information. Furthermore, the application of 3DNFC to pathological tissue achieves the 3D reconstruction for the unbiased analysis of diverse features of the disorders in their natural context. We suggest that 3DNFC is a promising volumetric imaging method for the prognosis and diagnosis of pathological tissues.

Endoscopic Ultrasound Localization Microscopy for the Evaluation of the Microvasculature of Gastrointestinal Tract Tumors in Rabbits.

The morphological and hemodynamic characterization of the microvascular network around the gastrointestinal (GI) tract can be of significant clinical value for the early diagnosis and treatment of GI tract cancer. Ultrasound localization microscopy (ULM) imaging has been demonstrated to be capable of resolving the microvascular network. However, the endoscopic application of ULM imaging techniques is still unknown. In this study, an endoscopic ultrasound localization microscopy (e-ULM) imaging technique was developed to evaluate the changes of microvasculature during GI tract tumor growth. A customized circular array transducer (center frequency: 6.8 MHz) and the coherent diverging wave compounding method were used to generate B-mode images. Spatiotemporal singular value decomposition processing was used to eliminate the background signals before signal localizations. The centroids of spatially isolated signals were localized and summed to generate the final super-resolution image. The final microvasculature map of a rabbit GI tract tumor reveals that e-ULM can be used to surpass the diffraction limit in traditional endoscopic ultrasound (EUS) imaging. Furthermore, it is observed that data from different stages of tumor growth exhibit significant differences in microvascular pattern and density. Our study demonstrated the implementation and application of an in vivo e-ULM imaging technique for the evaluation of the microvasculature of GI tumors. The efficient e-ULM imaging technique shows potential for use in the detection of GI tract tumor microcirculation changes and subsequent diagnosis of GI tract cancer.

Computed Tomography Intraoperative Navigation in Spinal Surgery: Assessment of Patient Radiation Exposure in Current Practices.

Patient radiation exposure associated with the use of computed tomography (CT) navigation during spinal surgeries was widely compared with other intraoperative imaging techniques. The aim of this study is to explore the use of navigation with regard to current spinal surgery practices and the technical limitations of such imaging systems. Dosimetric data from 101 patients who underwent intraoperative, CT-navigated spine surgery were retrospectively collected. The study population was divided into 3 groups according to the primary surgical indication. The number of CT image acquisitions per patient, the field length, and the time of exposure per acquisition during a single surgery were compared as well as the radiation dose emitted to patients. Dose-length products (DLP) per acquisition were 678.52, 656.8, and 649.36 mGy·cm with no significant difference for spinal deformity (SD), degenerative disease (DD), and vertebral fracture (VF) procedures, respectively. Analyzing the number of CT image acquisitions per patient revealed that repeated intraoperative scans were often performed for patients who were suffering from an SD due to technical limitations of the navigation. As a consequence, the cumulative dose was higher in the SD group (DLP total = 1175 mGy·cm) than in the DD (DLP total = 762.74 mGy·cm) and VF (DLP total = 649.36 mGy·cm) groups. CT navigation is an efficient intraoperative imaging technique that reduces the rate of surgical complications, but its technical limitations lead to an increased risk of patient radiation exposure, especially for complex surgeries where multiple scanning acquisitions are needed. To avoid patient's overexposure, spine surgeons should minimize the number of intraoperative acquisitions while considering the complexity of the surgery and the limitations of the guidance system. The use of dual guidance systems has also to be considered according to the benefit-risk balance between patient's outcomes and radiation dose exposure.

An intelligent deep convolutional network based COVID-19 detection from chest X-rays

Coronavirus disease-2019 (COVID-19) seems to be a fast spreading contagious illness that affects both humans and animals. This catastrophic deadly virus has an impact on people's daily lives, their wellbeing, and a nation's economy. According to a clinical research of COVID-19 affected patients, these individuals have been most commonly infected with a lung illness after coming into touch with the virus. A chest X-ray (also known as radiography) or a chest CT scan seems to be more efficient imaging techniques for detecting lung issues. Nonetheless, when compared to a chest CT, a significant chest X-ray remains a less expensive procedure. Thus, in this research, a novel Deep convolution neural network algorithm is presented to detect the COVID-19 from X-ray image. Moreover, to enhance diagnostics sensitivity and reduce error rate, a hybrid Two-step-AS clustering approach with Ensemble Bootstrap aggregating training and Multiple NN methods used. In addition, TSEBANN model has been employed to explore the qualification procedure effects. The proposed algorithm was trained before and after classification while compared to traditional Convolutional Neural Network (CNN). After, the process of pre-processing and feature extraction, the CNN strategy was adopted as an identification approach to categorize the information depending on Chest X-ray recognition. These examples were then classified using the CNN classification technique. The testing was conducted on the COVID-19 X-ray dataset, and the cross-validation approach was used to determine the model’s validity. The result indicated that a CNN system classification has attained an accuracy of 98.062 %.

An advantageous imaging perspective for quantitative evaluation of 7075 aluminum alloy grain boundary precipitates using scanning electron microscope.

7075 Aluminum alloy (AA7075) samples undergone four aging sequences were examined using a scanning electron microscope (SEM) and a transmitted electron microscope (TEM). The measurements results validate the correlation between stress corrosion cracking (SCC) resistance and the size and inter-distance of the grain boundary precipitates (GBPs). To evaluate the size and inter-distance of GBPs, we demonstrate in this study a highly efficient SEM imaging technique that can unfold grain boundary in a two-dimensional view. Compared to TEM, imaging with backscattered electrons in SEM (SEM-BSE) is more advantageous for GBPs presentation and measurements. The major reason is that about 900 times more sampling area can be imaged with SEM from the same specimen for TEM observation, thus enabling frequent appearances of GBPs at normal top view perspective, a planar view best for GBPs quantitative analysis but not well-documented. The acceleration tension of SEM for imaging was optimized at 10kV with an information depth of around 330 nm. RESEARCH HIGHLIGHTS: Scanning electron microscope (SEM) imaging using backscattered electrons is efficient for AA7075 grain boundary precipitate imaging. The precipitate size and inter-distance can be more accurately measured with the perspective of normal top view under SEM than transmitted electron microscope.

The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness.

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia's frequency-wavenumber (f-k), Lu's f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia's f-k, Lu's f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.

Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review.

Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.

Vessel-based hybrid optic disk segmentation applied to mobile phone camera retinal images.

Precise detection of the optic disk (OD) is an important task in the diagnosis of diabetic retinopathy. To manage the massive diabetic population, there is a significant demand for efficient and remote retinal imaging techniques. In this regard, the use of handheld mobile cameras attached to a smartphone is a promising approach. However, smartphone retinal images are often of low quality, compared to those obtained on standard equipment. They also have a narrow field of view and an incomplete/unbalanced vessel structure. Hence, we propose a new, fully automatic hybrid method for OD localization (HLM). It is designed for and verified on mobile camera/smartphone retinal images. The HLM analyzes the vessel structure and finds the OD locations by using the exclusion method when an image has a complete vessel system, and a newly proposed line detection method, otherwise. For OD segmentation, an active contour model followed by the circle fitting approach is integrated into the HLM. The proposed method was tested on three mobile camera datasets and four datasets obtained by standard equipment. For mobile camera datasets, the HLM achieves an average accuracy of 98% for OD localization. The segmentation routine obtains an average precision of 92.64% and an average recall of 82.38%. Testing against the recent state-of-the-art methods on the standard datasets shows comparable performance. The proposed framework for OD localization and segmentation designed for and verified on mobile camera retinal datasets and standard datasets. (EM - "Exclusion Method", LDM - "Line Detection Method", OD - "Optic Disk" and PPV - "Positive Predictive Value").

Value of Intravoxel Incoherent Motion (IVIM) Imaging for Differentiation between Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma.

Efficient noninvasive imaging techniques in the differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are very important because of their different management and prognosis. Our purpose was to evaluate the difference of parameters extracted from intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) between the two groups and their performance for the differentiation, as well as the significance of perfusion information. IVIM studies (9 b-values) in 41 patients with either ICC or HCC were reviewed retrospectively by two observers. Diffusion coefficient (D), pseudodiffusion coefficient (D∗), perfusion fraction (f), ADC, and the mean percentage of parenchymal enhancement (MPPE) at 30 s after contrast-enhancement were calculated and compared between ICC and HCC. The relationship between D∗, f values, and MPPE was evaluated by Spearman's correlation test. The diagnostic efficacy of all parameters was analyzed by the receiver operating characteristic (ROC) curve. Interobserver and intraobserver agreements were analyzed. The parameters (D and ADC) of ICC were distinctly higher than those of HCC; whereas the parameters (f and MPPE of arterial phase) were distinctly lower (all false discovery rate [FDR]-corrected P < 0.05). The metric D∗ value of ICC was slightly higher than that of HCC (71.44 vs 69.41) with FDR-corrected P > 0.05. Moreover, the value of parameter D was significantly lower than that of ADC (FDR-corrected P < 0.05). The parameters (D and f values) extracted from IVIM showed excellent diagnostic efficiency in the identification, and the diagnostic efficiency of D value was significantly higher than that of the ADC. There were positive correlations between perfusion-related parameters (D∗, f values) and MPPE. Interobserver and intraobserver agreements were excellent or perfect in measurements of all parameters. Parameters derived from IVIM were valuable for distinguishing ICC and HCC. Moreover, the D value showed better diagnostic efficiency for the differential diagnosis than monoexponential fitting-derived ADC value. Meanwhile, the significant correlation between perfusion-related parameters and MPPE demonstrates that specific IVIM metrics may serve as a noninvasive indicator for the vascular perfusion information of ICC and HCC.

Diagnostic accuracy of lung ultrasonography in childhood pneumonia: a meta-analysis.

This meta-analysis aimed to assess the diagnostic accuracy of lung ultrasonography in pneumonia-affected pediatric patients. Literature search of published articles in Medline, Web of Science, Scopus, Embase and Journal of Web till September 2020 were reviewed for the predescribed accuracy assessors. In compliance with the inclusion and exclusion criteria, two researchers independently screened the literature, collected the results and assessed the risks of bias using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. The pooled sensitivity and specificity, pooled positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were estimated for the meta-analysis. The overall efficiency of lung ultrasonography (LUS) was evaluated using a summary receiver operating characteristic curve. Q and I2 statistics were used to determine heterogeneity. Meta disc software was used for the analysis of the study. Out of 1182 studies, only 29 articles were chosen; 25 of them were prospective studies and 4 studies were retrospective. The overall pooled sensitivity was 0.83 [95% confidence intervals (CI), 0.81-0.84] and specificity was 0.84 (95% CI, 0.81-0.86), depicting good diagnostic performance. LUS is an efficient imaging technique for detecting childhood pneumonia with a high accuracy rate. It is an appealing alternative to chest X rays to detect and follow-up pneumonia in children because it is simple to do, widely available, comparatively cheap and free of radiation hazards.