Field Imaging Research Articles

Towards robust crop disease detection for complex real field background images

Most of the work done in image processing-based crop disease detection focuses on images with plain background. This paper presents a technique for crop disease detection for complex real field background images. A segmentation technique is presented to extract leaf patches from the entire image. Transform domain cepstral analysis is proposed for obtaining cepstral coefficients, to attain two level classifications. The first level classifies the crop species while the second level classifies the species into healthy leaf or leaf with specific type of disease. The work is tested on three crops Banana, Soybean and Grape and is checked on plain background laboratory images and on complex real field images. Suggested technique give species level accuracy of 94.33 %, 94.11 % and 98.44 % and disease level average accuracy of 97.75 %, 96.66 % and 97.95 % for Banana, Soybean and Grape, respectively. Comparison with standard features like texture and shape indicate that the presented technique gives the best results for both plain and complex background images suggesting its utilization in crop disease detection to reduce the agricultural and economic losses.

Two-Step Iterative Medical Microwave Tomography

In the field of medical imaging, microwave tomography (MWT) is based on the scattering and absorption characteristics of different tissues to microwaves and can reconstruct the electromagnetic property distribution of biological tissues non-invasively and without ionizing radiation. However, due to the inherently nonlinear and ill-posed characteristics of MWT calculations, actual imaging is prone to overfitting or artifacts. To address this, this paper proposes a two-step iterative imaging approach for rapid medical microwave tomography. This method establishes corresponding objective functions for microwave imaging across multiple frequencies and conducts iterative calculations on images at varying resolutions. This effectively enhances image clarity and accuracy while alleviating the issue of prolonged computational time associated with imaging complex structures at high resolution due to insufficient prior information during iterative processes. In the electromagnetic simulation section, we simulated a three-layer brain model and conducted imaging experiments. The results demonstrate that the algorithm significantly enhances imaging resolution, accurately pinpointing cerebral hemorrhages at different locations using an eight-antenna array and successfully reconstructs tomography images with a hemorrhage area radius of 1 cm. Lastly, experiments were conducted using a medical microwave tomography platform and four simplified human brain models, achieving millimeter-level accuracy in MWT.

Smartphone Aided Funduscopy in Albino Rabbits

Aims: The methodology, utility and clinical feasibility of using a smartphone camera to obtain images of ocular fundus of albino rabbits with ocular hypertension and normotension were studied. A comparative analysis of fundus images obtained from two popularly used smartphone models, android and iOS device was performed on 36 adult albino rabbits. Study Design: A cross-sectional study involving two cohorts of ocular hypertensive and normotensive albino rabbits. Place and Duration of Study: Department of Veterinary Surgery and Radiology, College of Veterinary and Animal Sciences, Mannuthy for an eight-week period (2023). Methodology: A total of 36 adult albino rabbits (18 males and 18 females; age range 6- 8 months of age) with ocular normotensive eyes and unilateral ocular hypertension-induced models were used. The conscious animals were gently restrained in an acrylic restrainer. Instillation of topical mydriatic solution (tropicamide 0.8% and phenylephrine 5%) facilitated visual examination and enhanced field of view along with auxiliary condensing lenses of 20 and 40 Diopters. A comparison of fundus images obtained from two popularly used smartphone models, android and iOS devices was performed on 36 adult albino rabbits. Results: Fundus images comprising the optic nerve head and peripapillary retina were obtained with adequate spatial resolution and detail. The variation between optic disc of ocular hypertensive eye revealed mild edema and cupping of optic disc. Normal merangiotic retina and optic disc were clearly obtained in normotensive rabbit eyes. The iOS device used in this case yielded better images in resolution and field of view compared to the android version used in this case. Conclusion: Smart phone funduscopy offered good detail in contrast and resolution even in amelanotic eyes of albino rabbits using inbuilt technology without the need for an external adapter or sophisticated additional software. It is an animal-friendly futuristic solution for digital documentation, telemedicine, teaching and clinical prognosis formulation.

Quantitative magnetooptical analysis using indicator films for the detection of magnetic field distributions, temperature, and electrical currents

The accurate characterization of local magnetic fields and temperature is vital for the design of electronic systems. To meet this imperative, we present a novel non-contact approach for simultaneous quantitative magnetic field imaging and temperature sensing using magnetooptics and a bismuth-doped yttrium iron garnet film with out-of-plane anisotropy. For the direct signal quantification, a Stokes polarization camera is employed in a conventional magnetooptical microscope. The magnetization in the garnet is modulated with an external magnetic field to continuously image the Faraday rotation at four distinct points along the saturating magnetization loop. The method enables sensing of the magnetooptical signal in saturation, the magnetooptical susceptibility, the temperature, and self-calibrated driftfree imaging of the out-of-plane magnetic field component. A spatial resolution of magnetic field in the micrometer range with millisecond exposure time is demonstrated. The method is verified by analyzing the stray magnetic field distribution of electrical current in a wire simultaneously to the Joule heating induced by the applied current.

Design a new scheme for image security using a deep learning technique of hierarchical parameters

Abstract With the continued exponential growth of digital images, concerns about the security and confidentiality of visual data have increased. In this session, a new developed approach was presented for image security and confidentiality by taking advantage of deep learning (DL) technology and producing data hierarchies. Due to the development taking place in the field of images and the large circulation of them through modern applications, it has become necessary to maintain their security. DL technology was used to encrypt and decrypt images, and based on hierarchical variables to complicate the encryption process. Convolutional neural networks are used in automatic learning to extract hierarchical features from an image, and to ensure adaptability, the model is trained on a variety of images. In order to encrypt the image, multi-layered hierarchical processes are used, and there are layers added during the work for complexity and to thwart attacks. Manipulating the layers of the neural network in a hierarchical manner to benefit from the outputs of the layers in feedback reflects the importance of the contributions here. Likewise, scattering the columns and rows of the image in a descending or ascending manner increases the efficiency of the contribution in this study. The use of hierarchical parameters facilitates encryption and decryption for authorized users. The evaluation of the research was conducted using established picture metrics and compared to pre-existing encryption techniques. The experimental findings substantiated the efficacy of the proposed approach in upholding image security, with the inclusion of hierarchical information further bolstering its ability to thwart attacks. Consequently, it emerges as a very promising strategy for ensuring image security. The proposed method is a significant advancement in creating an image security strategy using DL and a hierarchical variable creation process. The study provides a good and adaptable solution to evolving image security challenges in the digital age.

Preclinical Aspects of [89Zr]Zr-DFO-Rituximab: A High Potential Agent for Immuno-PET Imaging.

An early diagnosis of cancer can lead to choosing more effective treatment and increase the number of cancer survivors. In this study, the preparation and preclinical aspects of [89Zr]Zr-DFO-Rituximab, a high-potential agent for PET imaging of Non- Hodgkin Lymphoma (NHL), were evaluated. DFO was conjugated to rituximab monoclonal antibody (mAb), and DFO-rituximab was successfully labeled with zirconium-89 (89Zr) at optimized conditions. The stability of the complex was assessed in human blood serum and PBS buffer. Radioimmunoreactivity (RIA) of the radioimmunoconjugate (RIC) was evaluated on CD20-overexpressing Raji cell line and CHO cells. The biodistribution of the radiolabeled mAb was studied in normal and tumorbearing rodents. Finally, the absorbed dose in human organs was estimated. The radiolabeled compound was prepared with radiochemical purity (RCP) >99% (RTLC) and a specific activity of 180±1.8 GBq/g. The RCP of the final complex PBS buffer and human blood serum was higher than 95%, even after 48 h post incubation. The RIA assay demonstrated that more than 63% of the radiolabeled compound (40 ng/ml, 0.5 mL) was bound to 5×106 Raji cells. The biodistribution of the final product in tumor-bearing mice showed a high accumulation of the RIC in the tumor site in all intervals post-injection. Tumor/ non-target ratios were increased over time, and longer imaging time was suggested. The dosimetry data indicated that the liver received the most absorbed dose after the complex injection. [89Zr]Zr-DFO-Rituximab represents a significant advancement in the field of oncological imaging and offers a robust platform for both diagnostic and therapeutic applications in the management of B-cell malignancies.

Theoretical analysis and experiment verification in improvement of the new micro contour mode ultrasound transducer

Commercialized micro ultrasonic transducer generally adopts thickness mode to produce ultrasound radiation of thickness direction. The miniaturization of low-frequency transducer is a problem due to frequency inversely proportional to thickness of transducer. A new micro contour mode ultrasound transducer is proposed for satisfying miniaturization design. Theory analysis, FEM analysis and experimental investigation are carried out to verify the principle and improve the sound field distribution of contour mode transducer. Three kinds of contour transducers with width 300 μm, 600 μm, and 900 μm are fabricated and the reflecting house is added to improve lateral resolution. The performance is evaluated by electrical impedance, pulse-echo response tests and B-mode imaging tests with a 25 µm tungsten wire phantom. The corresponding experiment result of center frequency, −6 dB bandwidth and sensitivity are 4.1 MHz@37 %@4.5Vpp, 2.5 MHz@37 %@3.4Vpp, and 1.8 MHz@29 %@2.0Vpp respectively. Wire phantom imaging showed the lateral resolution has been markedly promoted with reflecting house. Compared with traditional thickness mode transducer, the proposed transducer can achieve smaller size with simplifying fabricated structure. It has a good application prospect in the fields of intervention image and therapy.

Off-axis freeform optical design for large curved field of view imaging

Recording neuron activities is pivotal for elucidating the functionality of the nervous system. However, the curved cortex surface of experimental mice presents a significant challenge for optical systems, particularly when a larger field of view (FOV) is required. To address this challenge, we have designed an off-axis three-mirror system that incorporates freeform surfaces on both the primary and secondary mirrors. This system achieves a large imaging FOV of 18°×9°, delivering near-diffraction-limit imaging quality across a curvature spectrum of −14.7 to −15.3mm. A manufacturability analysis indicates that the freeform surfaces are straightforward to produce, and the overall system demonstrates low sensitivity to tolerance and measurement errors. This study introduces a novel, to the best of our knowledge, solution to the field curvature constraints in optical imaging of cortical activity, providing substantial technical support for in vivo neuronal imaging endeavors.

Multiscale Characterization of Fractures and Analysis of Key Controlling Factors for Fracture Development in Tight Sandstone Reservoirs of the Yanchang Formation, SW Ordos Basin, China

Tight sandstone reservoirs, despite their low porosity and permeability, present considerable exploration potential as unconventional hydrocarbon resources. Natural fractures play a crucial role in hydrocarbon migration, accumulation, and present engineering challenges such as late-stage reformation in these reservoirs. This study examines fractures in the seventh member of the Triassic Yanchang Formation’s tight sandstone within the Ordos Basin using a range of methods, including field outcrops, core samples, imaging and conventional logging, thin sections, and scanning electron microscopy. The study clarifies the characteristics of fracture development and evaluates the relationship between dynamic and static rock mechanics parameters, including the calculation of the brittleness index. Primary factors influencing fracture development were quantitatively assessed through a combination of outcrop, core, and mechanical test data. Findings reveal that high-angle structural fractures are predominant, with some bedding and diagenetic fractures also present. Acoustic, spontaneous potential, and caliper logging, in conjunction with imaging data, enabled the development of a comprehensive probabilistic index for fracture identification, which produced favorable results. The analysis identifies four key factors influencing fracture development: stratum thickness, brittleness index, lithology, and rock mechanical stratigraphy. Among these factors, stratum thickness is negatively correlated with fracture development. Conversely, the brittleness index positively correlates with fracture development and significantly influences fracture length, aperture, and linear density. Fractures are most prevalent in siltstone and fine sandstone, with minimal development in mudstone. Different rock mechanics layer types also impact fracture development. These insights into fracture characteristics and controlling factors are anticipated to enhance exploration efforts and contribute to the study of similar unconventional reservoirs.

Integration of single-photon miniature fluorescence microscopy and electrophysiological recording methods for <i>in vivo</i> studying hippocampal neuronal activity

The miniature single-photon fluorescent microscope (miniscope) enables the visualization of calcium activity in vivo in freely moving laboratory animals, providing the capability to track cellular activity during the investigation of memory formation, learning, sleep, and social interactions. However, the use of calcium sensors for in vivo imaging is limited by their relatively slow (millisecond-scale) kinetics, which complicates the recording of high-frequency spike activity. The integration of methods from single-photon miniature fluorescent microscopy with electrophysiological recording, which possesses microsecond resolution, represents a potential solution to this issue. Such a combination of techniques allows for the simultaneous recording of optical and electrophysiological activity in a single animal in vivo. In this study, a flexible polyimide microelectrode was developed and integrated with the gradient lens of the miniscope. The in vivo tests conducted in this research confirmed that the microelectrode combined with the gradient lens facilitates simultaneous single-photon calcium imaging and local field potential recording in the hippocampus of an adult mouse.

Cr3+-Doped LiAlO2 NIR-I Emitting Phosphors with Superior Resistance to Thermal Quenching for Night Vision Monitoring and Bioimaging.

Near-infrared phosphor-converted light-emitting diodes (NIR pc-LEDs) as a new NIR light source has outstanding application potential in the fields of NIR spectroscopy analysis, sensing, imaging, and pattern recognition. Therefore, the development of NIR phosphors with good NIR luminescence thermal stability has attracted much attention. To this end, we developed LiAlO2:Cr3+ garnet-type NIR phosphors by a high-temperature solid-state reaction method. Under 405 nm excitation, the Cr3+ ions located in tetrahedrons of LiAlO2 emit NIR emission in a broadband NIR emission that covers 650-900 nm mixed with several sharp narrowband R-line emissions, which showed excellent luminescence thermal stability with integrated intensity of emission measured at 573 K is ∼90.86% of that measured at 303 K caused by good structural rigidity and low thermal expansion coefficient of the matrix material. An NIR pc-LED device assembled with the optimized LiAlO2:Cr3+ and a commercially available purple LED chip emitted NIR output power of ∼98.172 mW at a driving current of 300 mA and demonstrated an electro-optical conversion efficiency of ∼9.09%, while demonstrated it has excellent application potential in the fields of night vision monitoring and biomedical imaging.

Texture Analysis in Volumetric Imaging for Dentomaxillofacial Radiology: Transforming Diagnostic Approaches and Future Directions

This narrative review explores texture analysis as a valuable technique in dentomaxillofacial diagnosis, providing an advanced method for quantification and characterization of different image modalities. The traditional imaging techniques rely primarily on visual assessment, which may overlook subtle variations in tissue structure. In contrast, texture analysis uses sophisticated algorithms to extract quantitative information from imaging data, thus offering deeper insights into the spatial distribution and relationships of pixel intensities. This process identifies unique “texture signatures”, serving as markers for accurately characterizing tissue changes or pathological processes. The synergy between texture analysis and radiomics allows radiologists to transcend traditional size-based or semantic descriptors, offering a comprehensive understanding of imaging data. This method enhances diagnostic accuracy, particularly for the assessment of oral and maxillofacial pathologies. The integration of texture analysis with radiomics expands the potential for precise tissue characterization by moving beyond the limitations of human eye evaluations. This article reviews the current trends and methodologies in texture analysis within the field of dentomaxillofacial imaging, highlights its practical applications, and discusses future directions for research and dental clinical practice.

Deep Learning Approach for Arm Fracture Detection Based on an Improved YOLOv8 Algorithm

Artificial intelligence (AI)-assisted computer vision is an evolving field in medical imaging. However, accuracy and precision suffer when using the existing AI models for small, easy-to-miss objects such as bone fractures, which affects the models’ applicability and effectiveness in a clinical setting. The proposed integration of the Hybrid-Attention (HA) mechanism into the YOLOv8 architecture offers a robust solution to improve accuracy, reliability, and speed in medical imaging applications. Experimental results demonstrate that our HA-modified YOLOv8 models achieve a 20% higher Mean Average Precision (mAP 50) and improved processing speed in arm fracture detection.

Nanoradiopharmaceuticals: An Attractive Concept in Oncotherapy.

Radiopharmaceuticals are of significant importance in the fields of tumor imaging and therapy. In recent decades, the increasing role of nanotechnology has led to the attractive concept of nanoradiopharmaceuticals. Consequently, it is imperative to provide a concise summary of the necessary guidelines to facilitate the translation of nanoradiopharmaceuticals. In this work, we have presented the contents of radiolabeling strategies and some applications of nanoradiopharmaceuticals. Such a framework can assist researchers in identifying more pertinent insights or making more informed decisions in the study of nanoradiopharmaceuticals.

Neural Radiance Field Image Refinement through End‐to‐End Sampling Point Optimization

Neural radiance field (NeRF), capable of synthesizing high‐quality novel viewpoint images, suffers from issues like artifact occurrence due to its fixed sampling points during rendering. This study proposes a method that optimizes sampling points to reduce artifacts and produce more detailed images. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Ultralong Room-Temperature Phosphorescence in Ca(II) Metal-Organic Frameworks Based on Nicotinic Acid Ligands.

In recent years, metal-organic framework (MOF) materials with long persistent luminescence (LPL) have inspired extensive attention and presented various applications in security systems, information anticounterfeiting, and biological imaging fields. However, obtaining LPL materials with ultralong lifetime remains challenging. Halogen atoms, as nonmetallic elements existing in the frameworks, can not only induce the heavy-atom effect, effectively enhancing spin-orbit coupling and promoting intersystem crossing (ISC) processes, but also suppress non-radiative transition of the triplet states through the intra- and intermolecular interactions. Specifically, fluorine atoms with the strongest electronegativity may form intermolecular aggregate interlockings through halogen-bonding interactions that restrict molecular motions and vibrations, thereby improving phosphorescent lifetime. With the aforementioned considerations, two distinct types of MOFs with/without fluorine atoms (namely, Ca-MOF and 5FCa-MOF) were synthesized. Notably, by introducing fluorine atoms into MOFs, fluorine-induced intermolecular aggregate interlockings effectively enhanced the phosphorescent lifetime of 5FCa-MOF exceeding 264 ms compared to that of Ca-MOF (103.94 ms). Remarkably, both MOFs displayed bright LPL to the naked eye after removal of the irradiation source, especially 5FCa-MOF which can last for about 2 s. By introducing fluorine atoms, 5FCa-MOF exhibits greatly enhanced ISC with a rate constant up to 4.1 × 106 s-1 and suppressed non-radiative decay down to 3.73 s-1, thereby extending the LPL time. The thus obtained LPL provides potential in information encryption, security systems, optical anticounterfeiting, and so on.

Single layer vanadium oxide assisted switchable metasurfaces for transmissive and reflective polarization conversion

Polarization control using metasurfaces is highly advantageous; however, most metasurfaces operate exclusively in either transmission or reflection mode. Additionally, achieving both wide bandwidth and high efficiency simultaneously in their design remains a significant challenge. Here, we design a high-efficiency and wideband switchable metasurface that can switch between transmissive and reflective polarization conversion modes by utilizing a single layer of I-shaped resonators and gold-vanadium dioxide (VO2) alternating gratings printed on a quartz substrate. When VO2 transitions to its metallic phase, the continuous metal layers of gold-VO2 eliminate transmission and the designed metasurface operates as a reflective cross-polarization converter with a polarization conversion ratio (PCR) exceeding 0.9 over a broad frequency range of 1.4–3.3 THz. Conversely, when VO2 is in its insulator phase, the THz incoming wave can transmit through the gratings, and the design behaves as a transmissive cross-polarization converter with a PCR above 0.99 in the 0.75-4.0 THz range for a forward y- polarized wave. The working mechanism for both transmissive and reflective polarization conversion modes is explained through theoretical analysis and surface current distributions. With the advantages of facile design, high performance, and dual functionality, our design is expected to be applied in the fields of imaging, sensing, and communication.

Multi-function vortex array radar

In the realm of automation systems, multi-function radars serve as essential sensory components for self-driving vehicles and airbornes. Effective resource allocation management is crucial, requiring a high level of versatility to accomplish multiple tasks, especially, for increasingly miniaturized hardware. Here, we advance a balanced protocol for detecting, positioning, and tracking moving targets in real-time. Our protocol integrates efficient data processing methods with robust hardware. Specifically, detection signals are modulated by optical vortices for imaging, and real time processing of the image field facilitates target positioning and tracking. Moreover, the protocol extends its utility to serve as a topographic laser profiling system for natural landscapes, highlighting its adaptability. This adaptability and versatility well position the proposed protocol to support a wide range of applications, spanning self-driving vehicles and aerial systems, underscoring its potential significance across multiple platforms.

Comprehensive Characterization of Bi1.34Fe0.66Nb1.34O6.35 Ceramics: Structural, Morphological, Electrical, and Magnetic Properties

Recent research in solid-state physics and materials engineering focuses on the development of new dielectric materials, with bismuth-based pyrochlores being already extensively applied in communications technology for their excellent dielectric properties and relatively low sintering temperatures. Herein, the structural, morphological, electrical, and magnetic properties of Bi1.34Fe0.66Nb1.34O6.35 ceramic, prepared by the sol–gel method and sintered at 500 °C, are investigated. The Rietveld refinement of the XRD pattern showed a cubic phase belonging to the space group Fd-3m and a crystallite size of 42 nm. Transmission electron microscopy further confirmed the crystallite size and the homogeneous distribution of Bi, Fe, Nb, and O elements, as evidenced by high-angle annular dark field imaging and STEM-EDX mapping. The morphology of the sample, assessed by scanning electron microscopy, is characterized by submicron-sized spherical particles. Dielectric spectroscopic studies revealed that the dielectric properties, strongly influenced by frequency and temperature, indicate the material’s potential for energy storage due to lower dielectric loss compared to the dielectric constant. The observed relaxation phenomena, confirmed through variations in dielectric loss and loss tangent, highlight the influence of grain boundaries and temperature on electron hopping and charge carrier dynamics. Using SQUID magnetometry, we identified two distinct magnetic phases. The primary phase, corresponding to the Bi1.34Fe0.66Nb1.34O6.35 ceramic, exhibits an antiferromagnetic behavior below its Néel temperature at around 8.8 K. A secondary high-Curie temperature ferrimagnetic phase, likely vestigial maghemite and/or magnetite, was also detected, indicating an estimated fraction below 0.02 wt.%.

CNCAN: Contrast and normal channel attention network for super-resolution image reconstruction of crops and weeds

Numerous studies have been performed to apply camera vision technologies in robot-based agriculture and smart farms. In particular, to obtain high accuracy, it is essential to procure high-resolution (HR) images, which requires a high-performance camera. However, due to high costs it is difficult to widely apply the camera in agricultural robots. To overcome this limitation, we propose contrast and normal channel attention network (CNCAN) for super-resolution reconstruction (SR), which is the first research for the accurate semantic segmentation of crops and weeds even with low-resolution (LR) images captured by low-cost and LR camera. Attention block and activation function that considers high frequency and contrast information of images are used in CNCAN, and the residual connection method is applied to improve the learning stability.As a result of experimenting with three open datasets, namely, Bonirob, rice seedling and weed, and crop/weed field image (CWFID) datasets, the mean intersection of union (MIOU) results of semantic segmentation for crops and weeds with SR images through CNCAN were 0.7685, 0.6346, and 0.6931 in the Bonirob, rice seedling and weed, and CWFID datasets, respectively, confirming higher accuracy than other state-of-the-art methods for SR.