Showing papers on "Imaging technology published in 2019"

Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor

Abstract: Now-a-days image processing placed an important role for recognizing various diseases such as breast, lung, and brain tumors in earlier stage for giving the appropriate treatment. Presently, most cancer diagnosis worked according to the visual examination process with effectively. Human visual reviewing of infinitesimal biopsy pictures is exceptionally tedious, subjective, and conflicting due to between and intra-onlooker varieties. In this manner, the malignancy and it’s compose will be distinguished in a beginning time for finish treatment and fix. This brain tumor classification system using machine learning-based back propagation neural networks (MLBPNN) causes pathologists to enhance the exactness and proficiency in location of threat and to limit the entomb onlooker variety. Moreover, the technique may assist doctors with analyzing the picture cell by utilizing order and bunching calculations by recoloring qualities of the phones. The different picture preparing steps required for disease location from biopsy pictures incorporate procurement, upgrade, and division; include extraction, picture portrayal, characterization, and basic leadership. In this paper, MLBPNN is analyzed with the help of infra-red sensor imaging technology. Then, the computational multifaceted nature of neural distinguishing proof incredibly diminished when the entire framework is deteriorated into a few subsystems. The features are extracted using fractal dimension algorithm and then the most significant features are selected using multi fractal detection technique to reduce the complexity. This imaging sensor is integrated via wireless infrared imaging sensor which is produced to transmit the tumor warm data to a specialist clinician to screen the wellbeing condition and for helpful control of ultrasound measurements level, especially if there should arise an occurrence of elderly patients living in remote zones.

Reduced Reference Quality Assessment of Light Field Images

Abstract: Immersive media, such as free view point video and 360° video, are expected to be dominant as broadcasting services. The light field (LF) imaging is being considered as a next generation imaging technology offering the possibility to provide new services, including six degree-of-freedom video. The drawback of this technology is in the size of the generated content thus requiring novel compression systems and the design of ad-hoc methodologies for evaluating the perceived quality. In this paper, the relation between depth map quality and overall quality of LF image is studied. Next, a reduced reference quality assessment metric for LF images is presented. To predict the quality of distorted LF images, the measure of distortion in the depth map is exploited. To test and validate the proposed framework, a subjective experiment has been performed, and a LF image quality dataset has been created. The dataset is also used for evaluating the performance of state-of-the-art quality metrics, when applied to LF images. The achieved results evidence that the estimated quality score by the proposed framework has a significant correlation with subjective quality rating. Consequently, reference data can be delivered to the clients thus allowing the local estimation of the perceived quality of service.

Sparse Fourier single-pixel imaging.

Abstract: Fourier single-pixel imaging is one of the main single-pixel imaging techniques. To improve the imaging efficiency, some of the recent method typically select the low-frequency and discard the high-frequency information to reduce the number of acquired samples. However, sampling only a small amount of low-frequency components will lead to the loss of object details and will reduce the imaging resolution. At the same time, the ringing effect of the restored image due to frequency truncation is significant. In this paper, a new sparse Fourier single-pixel imaging method is proposed that reduces the number of samples explorations while maintaining increased image quality. The proposed method makes a special use of the characteristics of the Fourier spectrum distribution based on which the power of image information decreases gradually from low to high frequencies in the Fourier space. A variable density random sampling matrix is employed to achieve random sampling with Fourier single-pixel imaging technology, followed by the processing of the sparse Fourier spectra using compressive sensing algorithms to recover the high-quality information of the object. The new algorithm can effectively improve the quality of object restoration comparing with the existing Fourier single-pixel imaging methods which only acquire the low-frequency parts. Additionally, considering that the resolution of the system is diffraction limited, super-resolution imaging can also be achieved. Experimental results demonstrate the mainly correctness but also effectiveness of the proposed method.

Photoacoustic elastography imaging: a review.

Abstract: Elastography imaging is a promising tool-in both research and clinical settings-for diagnosis, staging, and therapeutic treatments of various life-threatening diseases (including brain tumors, breast cancers, prostate cancers, and Alzheimer's disease). Large variation in the physical (elastic) properties of tissue, from normal to diseased stages, enables highly sensitive characterization of pathophysiological states of the diseases. On the other hand, over the last decade or so, photoacoustic (PA) imaging-an imaging modality that combines the advantageous features of two separate imaging modalities, i.e., high spatial resolution and high contrast obtainable, respectively, from ultrasound- and optical-based modalities-has been emerging and widely studied. Recently, recovery of elastic properties of soft biological tissues-in addition to prior reported recovery of vital tissue physiological information (Hb, HbO2, SO, and total Hb), noninvasively and nondestructively, with unprecedented spatial resolution (μm) at penetration depth (cm)-has been reported. Studies demonstrating that combined recovery of mechanical tissue properties and physiological information-by a single (PA) imaging unit-pave a promising platform in clinical diagnosis and therapeutic treatments. We offer a comprehensive review of PA imaging technology, focusing on recent advances in relation to elastography. Our review draws out technological challenges pertaining to PA elastography (PAE) imaging, and viable approaches. Currently, PAE imaging is in the nurture stage of its development, where the technology is limited to qualitative study. The prevailing challenges (specifically, quantitative measurements) may be addressed in a similar way by which ultrasound elastography and optical coherence elastography were accredited for quantitative measurements.

An evidence-based approach to the routine use of optical coherence tomography.

Abstract: Optical coherence tomography is an imaging technology that has revolutionised the detection, assessment and management of ocular disease. It is now a mainstream technology in clinical practice and is performed by non-specialised personnel in some settings. This article provides a clinical perspective on the implications of that movement and describes best practice using multimodal imaging and an evidence-based approach. Practical, illustrative guides on the interpretation of optical coherence tomography are provided for three major diseases of the ocular fundus, in which optical coherence tomography is often crucial to management: age-related macular degeneration, diabetic retinopathy and glaucoma. Topics discussed include: cross-sectional and longitudinal signs in ocular disease, so-called 'red-green' disease whereby clinicians rely on machine/statistical comparisons for diagnosis in managing treatment-naive patients, and the utility of optical coherence tomography angiography and machine learning.

Optical diagnosis of colorectal polyps with Blue Light Imaging using a new international classification.

Abstract: BackgroundBlue Light Imaging (BLI) is a new imaging technology that enhances mucosal surface and vessel patterns. A specific BLI classification was recently developed to enable better characterisat...

Large-scale 3D imaging of insects with natural color.

Abstract: High-resolution 3D imaging technology has found a number of applications in many biological fields. However, the existing 3D imaging tools are often too time-consuming to use on large-scale specimens, such as centimeter-sized insects. In addition, most 3D imaging systems discard the natural color information of the specimens. To surmount these limitations, we present a structured illumination-based approach capable of delivering large field-of-view three-dimensional images. With this approach, 580nm lateral resolution full-color 3D images and 3D morphological data in the size range of typical insect samples can be obtained. This method provides a promising approach that can be used to support many different types of entomological investigations, including taxonomy, evolution, bionics, developmental biology, functional morphology, paleontology, forestry, etc.

Synthetic Aperture Radar Three-Dimensional Imaging——From TomoSAR and Array InSAR to Microwave Vision

Abstract: Synthetic Aperture Radar three-dimensional (SAR 3D) imaging technology can eliminate severe overlap in 2D images, and improve target recognition and 3D modeling capabilities, which have become an important trend in SAR development. After decades of development of SAR 3D imaging technology, many types of 3D imaging methods have been proposed. In this study, the history of SAR 3D imaging technology is systematically reviewed and the characteristics of existing SAR 3D imaging technology are analyzed. Given that the 3D information contained in SAR echo and images is not fully used by existing techniques, a new concept of SAR microwave vision 3D imaging has been proposed for the first time. This new concept is integrated with microwave scattering mechanism and image visual semantics to realize three-dimensional reconstruction, which form the theory and method of SAR microwave vision 3D imaging and can achieve high-efficiency and low-cost SAR 3D imaging. This study also analyzes the concept, goal and key scientific problems of SAR microwave vision 3D imaging and provides a preliminary solution, which will contribute in several ways to our understanding of SAR 3D imaging and provide the basis for further research.

Congenital and Structural Heart Disease Interventions Using Echocardiography-Fluoroscopy Fusion Imaging.

Abstract: With the increasing frequency of catheter-based interventions in congenital heart disease and structural heart disease, the use of fusion imaging has become a major enhancement for understanding complex anatomy and facilitating key steps in interventional procedures. Because transesophageal echocardiography and fluoroscopy are displayed in different visual perspectives, the interventional cardiologist must mentally reregister the images from the two modalities during the procedure. Echocardiography-fluoroscopy fusion (EFF) imaging displays the x-ray and ultrasound overlay images in the same visual perspective. This new technology allows for enhanced team communication, improved visual guidance, and more efficient navigation. The purpose of this review is to describe the EFF imaging technology, current uses of EFF imaging in congenital and structural heart disease, and future directions that will enhance this unique imaging technology to guide interventional procedures.

Imaging of Temporal Bone

Abstract: Multidetector computed tomography has been the benchmark for visualizing bony changes of the ear, but has recently been challenged by cone-beam computed tomography. In both methods, all inner ear bony structures can be visualized satisfactorily with 2D or 3D imaging. Both methods produce ionizing radiation and induce adverse health effects, especially among children. In 3T magnetic resonance imaging, the soft tissue can be imaged accurately. Use of gadolinium chelate (GdC) as a contrast agent allows the partition of fluid spaces to be visualized, such as the bulging of basilar and Reissner's membranes. Both intravenous and intratympanic administration of GdC has been used. The development of positive endolymph imaging method, which visualizes endolymph as a bright signal, and the use of image subtraction seems to allow more easily interpretable images. This long-awaited possibility of diagnosing endolymphatic hydrops in living human subjects has enabled the definition of Hydropic Ear Disease, encompassing typical Meniere's disease as well as its monosymptomatic variants and secondary conditions of endolymphatic hydrops. The next challenge in imaging of the temporal bone is to perform imaging at the cellular and molecular levels. This chapter provides an overview of current temporal bone imaging methods and a review of emerging concepts in temporal bone imaging technology.

Unsupervised Retina Image Synthesis via Disentangled Representation Learning

Abstract: Fluorescein Fundus Angiography (FFA) is an effective and necessary imaging technology for many retinal diseases including choroiditis, preretinal hemorrhage, and diabetic retinopathy. However, due to the invasive operation, harmful fluorescein dye, and the consequent side effects and complications, it is also an image modality that both doctors and patients are reluctant to use. Therefore, we propose an approach to use Fluorescein Fundus (FF) images, which are non-invasive and safe, to synthesize the invasive and harmful FFA images. Additionally, since paired data are rare and time-consuming to get, the proposed method uses unpaired data to synthesize FFA images in an unsupervised way. Previous unpaired image synthesis methods treat image translation between two domains in two separate ways and thus ignore the implicit feature correlation in the translation process. To solve that, the proposed method first disentangles domain features into domain-shared structure features and domain-independent appearance features. Guided by the adversarial learning, two generators will learn to synthesize FFA-like images and FF-like images correspondingly. Perceptual loss are introduced to preserve the content consistency during translation. Qualitative results show that our model could generate realistic and mimic images without the usage of paired data. We also make quantitative comparisons on Isfahan MISP dataset to demonstrate the superior image quality of the synthetic images.

Video image target monitoring based on RNN-LSTM

Abstract: Traditional image object classification and detection algorithms and strategies cannot meet the problem of video image acquisition and processing. Deep learning deliberately simulates the hierarchical structure of human brain, and establishes the mapping from low-level signals to high-level semantics, so as to achieve hierarchical feature representation of data. Deep learning technology has powerful visual information processing ability, which has become the forefront technology and domestic and international research hotspots to deal with this challenge. In order to solve the problem of target space location in video surveillance system, time-consuming and other problems, in this paper, we propose the algorithm based on RNN-LSTM deep learning. At the same time, according to the principle of OpenGL perspective imaging and photogrammetry consistency, we use 3D scene simulation imaging technology, relying on the corresponding relationship between video images and simulation images we locate the target object. In the 3D virtual scene, we set up the virtual camera to simulate the imaging processing of the actual camera, and the pixel coordinates in the video image of the surveillance target are substituted into the simulation image, next, the spatial coordinates of the target are inverted by the inverse process of the virtual imaging. The experimental results show that the detection of target objects has high accuracy, which has an important reference value for outdoor target localization through video surveillance images.

An improved scheme and numerical simulation of segmented planar imaging detector for electro-optical reconnaissance

Abstract: Segmented planar photoelectric detection imaging technology is a cutting-edge photoelectric imaging technology developed to realize the miniaturization and weight reduction of imaging systems. The imaging process of the integrated optical interferometry system was simulated by a computer simulation algorithm, and the influence of the system’s structural parameters on the imaging results was explored. Moreover, an optimal scheme of the baseline matching method was proposed. The simulation results showed that increasing the number of interferometer arms and baselines can improve the imaging quality of the system. The proposed baseline matching optimization method could improve the low-frequency sampling rate of the system and thus, improve the imaging quality. In addition, simulation results also gave the optimal imaging distance of the system, which indicates that the system is most suitable for remote sensing imaging, meanwhile measuring the system’s tolerance limit to phase noise. The requirements for the precision of waveguide fabrication are given, which play a guiding role in system manufacturing.

Imaging, Visualization, and Computation in Developmental Biology

Abstract: Embryonic development is highly complex and dynamic, requiring the coordination of numerous molecular and cellular events at precise times and places. Advances in imaging technology have made it po...

Advanced imaging technology applications in cytology

Abstract: Novel techniques have been developed to image cells at cellular and subcellular levels. They allow images to be analyzed with ultra-high resolution, in 2D and/or 3D. Several of these tools have been tested on cytology specimens demonstrating emerging applications that are likely to change the field of cytopathology. This review covers several of these advanced imaging methods. The use of optical coherence tomography to perform optical biopsies during endoscopic ultrasound procedures or visualize cells within effusion samples is discussed. The potential for quantitative phase microscopy to accurately screen Pap test slides or resolve indeterminate diagnoses in urine cytology is reviewed. The article also examines the application of 3D cytology using LuCED for lung cancer detection in sputum samples and the feasibility of imaging flow and mass cytometry to measure multiple biomarkers at the single cell level. Although these novel technologies have great potential, further research is necessary to validate their routine use in cytopathology practice.

Fully Integrated Solutions for High Resolution Terahertz Imaging (Invited)

Abstract: This paper is an overview of the advances of the integrated sub-THz/THz imaging technology. The challenges to implement fully integrated imaging systems at this frequency range are discussed and solutions to overcome them are presented. We review the design of a 320 GHz transmission based coherent imaging transceiver fabricated in 130 nm SiGe BiCMOS technology. The optimum design of the terahertz radiator in this work is discussed and the measurement results are provided. Next, we present the implementation of a fully integrated reflection-based FMCW imaging radar which operates at 170 GHz. In order to provide a wideband chirp, we provide a design technique to maximize the tuning bandwidth of the VCO. We also review a FMCW radar at 220 GHz with 62GHz of bandwidth, where we use the Inverse Synthetic Aperture Radar technique to reconstruct high resolution 2D and 3D images. We conclude the paper by a brief overview of the other available THz imaging techniques, and suggest emerging methods for a real-time THz imaging system.

Advances in whole body MRI for musculoskeletal imaging: Diffusion-weighted imaging.

Abstract: Recent advances in imaging technology have enabled the acquisition of anatomical and functional imaging from head to toe in a reasonably short scan time. Accordingly, whole body magnetic resonance imaging (WB-MRI) and diffusion-weighted imaging (WB-DWI) have gained recent attention for the management of musculoskeletal problems such as bone tumors and rheumatologic diseases. WB-MRI is especially useful in diagnosing systemic or widespread disease requiring whole body evaluation, such as bone metastases, multiple myeloma, lymphoma, neurofibromatosis, and spondyloarthropathies. Among WB-MRI sequences, the WB-DWI technique greatly increases the value of WB-MRI in the evaluation of disease extent and characterization as well as treatment monitoring. In support of the utilization of WB-MRI and WB-DWI in orthopedic clinics for various musculoskeletal diseases, we provide an overview of the technical aspects of WB-MRI and WB-DWI and their clinical applications in musculoskeletal tumors and rheumatic diseases.

Optimizing imaging and reducing radiation exposure during complex aortic endovascular procedures.

Abstract: Improvements in endovascular technologies and development of custom-made fenestrated and branched endografts currently allow clinicians to treat complex aortic lesions such as thoraco-abdominal and aortic arch aneurysms once treatable with open repair only. These advances are leading to an increase in the complexity of endovascular procedures which can cause long operation times and high levels of radiation exposure. This in turn places pressure on the vascular surgery community to display more superior interventional skills and radiological practices. Advanced imaging technology in this context represents a strong pillar in the treatment toolbox for delivering the best care at the lowest risk level. Delivering the best patient care while managing the radiation and iodine contrast media risks, especially in frail and renal impaired populations, is the challenge aortic surgeons are facing. Modern hybrid rooms are equipped with a wide range of new imaging applications such as fusion imaging and cone-beam computed tomography (CBCT). If these technologies contribute to reducing radiation, they can be complex and intimidating to master. The aim of this review is to discuss the fundamentals of good radiological practices and to describe the various imaging tools available to the aortic surgeon, both those available today and those we anticipate will be available in the near future, from equipment to software, to perform safe and efficient complex endovascular procedures.

Intelligent Imaging Technology in Diagnosis of Colorectal Cancer Using Deep Learning

Abstract: In order to explore the application of deep learning based intelligent imaging technology in the diagnosis of colorectal cancer, Tangdu Hospital patients are selected as the research object in this study. By scanning the cancer sites, then distinguishing and extracting the features of the tumors, the collected data are input into the designed in-depth learning intelligent assistant diagnosis system for comparison. The results show that in the analysis of image prediction accuracy, the best prediction accuracy of T1-weighted image method is matrix GLCM (gray level co-occurrence matrix) algorithm, the best prediction accuracy of adding T1-weighted image method is matrix MGLSZM (multi-gray area size matrix) algorithm, and the best prediction accuracy of T2-weighted image method is ALL combination of all texture features, and the best prediction accuracy of three imaging sequences is not more than 0.8. In the AUC analysis of the area under the curve of different texture features, it is found that T2-weighted imaging method has obvious advantages in differentiating colorectal cancer from other methods. Therefore, through this study, it is found that in the use of deep learning intelligent assistant diagnosis system for the diagnosis of colorectal cancer, it can provide useful information for the clinical diagnosis of colorectal cancer to a certain extent. Although there are some deficiencies in the research process, it still provides experimental basis for the diagnosis and treatment of colorectal cancer in later clinical stage.

Feasibility of prostatectomy without prostate biopsy in the era of new imaging technology and minimally invasive techniques

Abstract: Feasibility of prostatectomy without prostate biopsy in the era of new imaging technology and minimally invasive techniques

Image Infusion of Photoacoustic Imaging Based on Novel Adjustable Hand-held Probe

Abstract: Photoacoustic imaging (PAI) is developing rapidly as a new kind of imaging technology. Conventional photoacoustic imaging devices are expensive, cumbersome, and illumination schemes are not adjustable, which significantly limit their development in clinical application. We designed an automated hand-held PA probe with adjustable illumination angle, spot size and distance. We also developed an adaptive control system for controlling the probe to achieve optimum illumination. Simulated scanning process on human brain model is performed to obtain photoacoustic images at various locations. Through image fusion algorithm, the images of each position are spliced and fused. Finally, the infused PA image of the human brain is obtained with higher contrast and fidelity.

A bayesian mark interaction model for analysis of tumor pathology images.

Abstract: With the advance of imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis. This process produces massive imaging data that capture histological details in high resolution. Recent developments in deep-learning methods have enabled us to identify and classify individual cells from digital pathology images at large scale. Reliable statistical approaches to model the spatial pattern of cells can provide new insight into tumor progression and shed light on the biological mechanisms of cancer. We consider the problem of modeling spatial correlations among three commonly seen cells observed in tumor pathology images. A novel geostatistical marking model with interpretable underlying parameters is proposed in a Bayesian framework. We use auxiliary variable MCMC algorithms to sample from the posterior distribution with an intractable normalizing constant. We demonstrate how this model-based analysis can lead to sharper inferences than ordinary exploratory analyses, by means of application to three benchmark datasets and a case study on the pathology images of $188$ lung cancer patients. The case study shows that the spatial correlation between tumor and stromal cells predicts patient prognosis. This statistical methodology not only presents a new model for characterizing spatial correlations in a multitype spatial point pattern conditioning on the locations of the points, but also provides a new perspective for understanding the role of cell–cell interactions in cancer progression.

A Review of New and Emerging Techniques For Optical Diagnosis of Colonic Polyps.

Abstract: Background and aims Endoscopic imaging is a rapidly progressing field and benefits from miniaturization of advanced imaging technologies, which may allow accurate real-time characterization of lesions. The concept of the "optical biopsy" to predict polyp histology has gained prominence in recent years and may become clinically applicable with the advent of new imaging technology. This review aims to discuss current evidence and examine the emerging technologies as applied to the optical diagnosis of colorectal polyps. Methods A structured literature search and review has been carried out of the evidence for diagnostic accuracy of image-enhanced endoscopy and emerging endoscopic imaging technologies. The image-enhanced endoscopy techniques are reviewed, including their basic scientific principles and current evidence for effectiveness. These include the established image-enhancement technologies such as narrow-band imaging, i-scan, and Fuji intelligent chromoendoscopy. More recent technologies including optical enhancement, blue laser imaging, and linked color imaging are discussed. Adjunctive imaging techniques in current clinical use are discussed, such as autofluorescence imaging and endocytoscopy. The emerging advanced imaging techniques are reviewed, including confocal laser endomicroscopy, optical coherence tomography, and Raman spectroscopy. Conclusions Large studies of the established image-enhancement techniques show some role for the optical diagnosis of polyp histology, although results have been mixed, and at present only the technique of narrow-band imaging is appropriate for the diagnosis of low-risk polyps when used by an expert operator. Other image-enhancement techniques will require further study to validate their accuracy but show potential to support the use of a "resect-and-discard" approach to low-risk polyps. New technologies show exciting potential for real-time diagnosis, but further clinical studies in humans have yet to be performed.

3D H-scan ultrasound imaging system and method for acoustic scatterer size estimation: Preliminary studies using phantom materials

Abstract: H-scan ultrasound (US) is an innovative real-time imaging technology that depicts the relative size of acoustic scattering objects and structures. The purpose of this research was to develop a novel 3-dimensional (3D) H-scan US imaging approach for tissue classification in volume space. Using a programmable research scanner (Vantage 256, Verasonics Inc, Kirkland, WA) equipped with a custom-built volumetric imaging transducer (4DL7, Vermon, Tours, France), radio frequency (RF) data was collected for offline processing. H-scan US images were constructed after applying a set of convolutional filters based on Gaussian-weighted Hermite polynomials. These functions are related to different sized scattering objects. Preliminary studies were conducted using homogeneous gelatin-based tissue-mimicking phantom materials embedded with acoustic scatterers of varying size (15, 30 or 250 μm) and concentrations (0.1, 0.3, 0.5 or 1.0 %). In vitro results indicate that 3D H-scan US imaging can detect acoustic scatterers of varying size (p 0.05). Overall, our preliminary in vitro findings reveal that 3D H-scan US imaging allows the visualization of different tissue scatterer patterns.

Research on incoherent self-interference digital holography imaging technology

Abstract: An incoherent self -interference digital holography imaging system based on Michelson interferometer was reported. The system recorded the holograms of USAF1951 resolution target, onion epidermal cell and herbaceous stem crosscut. Reconstructing the captured hologram by three -step generalized phase shift can effectively eliminate zero-order images and twin images, and obtain a high resolution reconstructed image. The element three in group nine on the USAF1951 resolution target can be clearly seen, with a resolution of 645 lp/mm. The effect of diffraction distance on the quality of reconstructed image was studied by analyzing the relationship between them. Moreover, a 3D image of the object can be obtained by this system through reconstruction of the hair hologram.