Images Of Different Stages Research Articles

The value of oral contrast-enhanced gastric ultrasonography in the diagnosis and staging of benign peptic ulcer

We evaluate the value of oral contrast-enhanced gastric ultrasonography (OCUS) by comparing it with conventional gastroscopy in diagnosing and staging benign peptic ulcer. From July 2018 to December 2020, 44 patients with gastroscopy-confirmed benign peptic ulcers (a total of 45 ulcers were detected), who also received OCUS, were retrospectively reviewed. Each patient’s ultrasound images were compared with gastroscopy and pathology findings. The characteristics of ultrasonic images of different stages of ulcer were analysed. A total of 43 ulcers were detected by OCUS in 44 patients with benign peptic ulcers. There were no false positive results among the OCUS exams, but two ulcers were misdiagnosed. OCUS for benign peptic ulcer staging also shows acceptable clinical practice results. OCUS is useful for detecting and staging benign peptic ulcer, and may be considered an alternative method for conventional gastroscopy. OCUS is especially useful in the follow-up of BPU treatment, but futher study is needed to improve the diagnostic accuracy of benign and malignant ulcers.

This study addresses the challenge of intelligent diagnosis in Alzheimer's Disease by employing machine learning to classify MRI images depicting various disease stages. The author conducted a comparative analysis to assess the efficacy of diverse models

This study addresses the challenge of intelligent diagnosis in Alzheimer's Disease by employing machine learning to classify MRI images depicting various disease stages. The author conducted a comparative analysis to assess the efficacy of diverse models for this purpose, yielding several key findings. The primary model utilized in the research is founded on ResNet152V2, encompassing 152 pre-trained layers, 1 GlobalAveragePooling2D layer, 3 dropout layers, 3 dense layers, and 1 output layer. The research aims to achieve precise classification of MRI images corresponding to distinct Alzheimer's Disease stages, a pivotal step for early detection and intervention. To achieve this, this research adjusted the structure of the original model and changed some of the parameters and compared their results. Based on the results obtained, the author drew several conclusions. The author found that setting a larger value for the "patience" parameter in the Early Stopping callback helps avoid stopping the training process too early. Additionally, the author observed that the original model with only 2 fully connected layers was not stable enough in terms of gradient descent, indicating the need for additional fully connected layers. In conclusion, this research paper addressed the problem of classifying MRI images of different stages of Alzheimer's Disease using machine learning techniques. The comparative study of different models provided insights into the performance and potential improvements of the classification taskt.

3D Pre-Processing Algorithm for MRI Images of Different Stages of AD

Alzheimer’s disease (AD) is a degenerative neuronal brain disorder resulting in memory loss, skills, and cognitive changes. The disorder’s primary diagnostic tests are defined as total brain atrophy and hippocampal atrophy. Early diagnosis is significant, and automatic systems design is necessary for this disorder. Potential biomarkers for AD are described using a hippocampal magnetic resonance imaging volumetry system with certain limitations. For the definite identification of the hippocampus region, pre-processing of the 3D MRI images of AD is necessary. The filtering and histogram-based pre-processing techniques enhance the region of interest, which helps in effectively segmenting the biomarker, the hippocampus. The median and eight histogram clippings are defined to be 98% efficient pre-processing techniques with the comparison of image quality parameters and statistical analysis. Thus an algorithm for pre-processing of the 3D MRI images of stages of AD is designed for the further process of identification.

Detecting Wheat Heads from UAV Low-Altitude Remote Sensing Images Using Deep Learning Based on Transformer

The object detection method based on deep learning convolutional neural network (CNN) significantly improves the detection performance of wheat head on wheat images obtained from the near ground. Nevertheless, for wheat head images of different stages, high density, and overlaps captured by the aerial-scale unmanned aerial vehicle (UAV), the existing deep learning-based object detection methods often have poor detection effects. Since the receptive field of CNN is usually small, it is not conducive to capture global features. The visual Transformer can capture the global information of an image; hence we introduce Transformer to improve the detection effect and reduce the computation of the network. Three object detection networks based on Transformer are designed and developed, including the two-stage method FR-Transformer and the one-stage methods R-Transformer and Y-Transformer. Compared with various other prevalent object detection CNN methods, our FR-Transformer method outperforms them by 88.3% for AP50 and 38.5% for AP75. The experiments represent that the FR-Transformer method can gratify requirements of rapid and precise detection of wheat heads by the UAV in the field to a certain extent. These more relevant and direct information provide a reliable reference for further estimation of wheat yield.

Inspiratory and Expiratory Chest High-resolution CT: Small-airway Disease Evaluation in Patients with COVID-19.

An outbreak of coronavirus disease 2019 (COVID-19) has occurred worldwide. However, the small-airway disease in patients with COVID-19 has not been explored. This study aimed to explore the small-airway disease in patients with COVID-19 using inspiratory and expiratory chest high-resolution computed tomography (CT). This multicenter study included 108 patients with COVID-19. The patients were classified into five stages (0-IV) based on the CT images. The clinical and imaging data were compared among CT images in different stages. Patients were divided into three groups according to the time interval from the initial CT scan, and the clinical and air trapping data were compared among these groups. The correlation between clinical parameters and CT scores was evaluated. The clinical data, including age, frequency of breath shortness and dyspnea, neutrophil percentage, lymphocyte count, PaO2, PaCO2, SaO2, and time interval between the onset of illness and initial CT, showed significant differences among CT images in different stages. A significant difference in the CT score of air trapping was observed between stage I and stage III. A low negative correlation was found between the CT score of air trapping and the time interval between the onset of symptoms and initial CT. No significant difference was noted in the frequency and CT score of air trapping among different groups. Some patients with COVID-19 developed small-airway disease. Air trapping was more distinguished in the early stage of the disease and persisted during the 2-month follow-up. Longer-term follow-up studies are needed to confirm the findings.

Indocyanine green angiography imaging findings in artery occlusions

To describe the multimodal imaging features including indocyanine green angiography (ICGA) in cases diagnosed clinically as central retinal artery occlusion (CRAO) at its different disease stages. In this retrospective observational study, patients diagnosed clinically as CRAO or hemi-CRAO were included. All patients underwent multimodal imaging with optical coherence tomography (OCT), fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA) were studied. Analysis of ICGA images in different stages of artery occlusions and its correlation with accompanying FFA and OCT images was done. Eight such studies in five patients were available for analysis. The most important observation noted on ICGA was the presence of hypercyanescent spots seen during the acute stages of the disease in four of the five cases. The spots were accompanied by retinal vessel staining on FFA in the corresponding region. As the disease showed signs of resolution, the hypercyanescent spots on ICGA and retinal vessel staining on FFA disappeared. The hypercyanescent spots seen on the ICGA were noted due to the red blood cell aggregation or 'rouleaux' formation. In addition, choroidal perfusion abnormalities were noted on ICGA in all five cases in the acute stage. Choroidal perfusion changes can be identified in acute phase of retinal artery occlusion. Rouleaux formation in the retinal circulation occurs due to the slowing of the blood flow following artery occlusion. These are seen as hypercyanescent spots in the late phase on ICGA.

Three-dimensional construction of micrometer level in rat stomach by synchrotron radiation

BackgroundThe structural changes of gastric mucosa are considered as an important window of early gastric lesions. This article shows an imaging method of the stomach that does not use imaging agents. X-ray phase-contrast images of different stages of gastric development were taken using micrometer level X-ray in-line phase-contrast imaging (XILPCI) technique on synchrotron radiation facility. The aim of the study was to demonstrate that the imaging technique is an appropriate method for micron imaging of the gastric structures.MethodsThe stomachs of 4-, 6- and 12-week-old rats were removed and cleaned. XILPCI has 1000 times greater soft tissue contrast than that of X-ray traditional absorption radiography. The projection images of the rats stomachs were recorded by an XILPCI charge coupled device (CCD) at 9-μm image resolution.ResultsThe X-ray in-line phase-contrast images of the different stages of rats’ gastric specimens clearly showed the gastric architectures and the details of the gastro-duodenal region. 3-dimensional (3D) stomach anatomical structure images were reconstruction.ConclusionThe reconstructed gastric 3D images can clearly display the internal structure of the stomach. XILPCI may be a useful method for medical research in the future.

Segmentation and Registration of the Liver in Dynamic Contrast-Enhanced Computed Tomography Images

Dynamic contrast-enhanced computed tomography (DCE-CT) is the main auxiliary diagnostic tool for liver diseases. Liver segmentation and registration in all stages of DCE-CT images are the key technology for big data analysis of liver disease diagnosis. The change of imaging conditions in different stages of DCE-CT brings enormous challenges to the segmentation of liver CT images. This study proposes an automatic model for liver segmentation from abdominal CT images in different stages of DCE on the basis of U-Net. The skip connection in U-Net can improve the ability of complex feature recognition. A total of 4863 CT slices from 16 patients with hepatocellular carcinoma (HCC) were selected as the training set, and 1754 CT slices from 6 patients with HCC were selected as the test set. The training and test sets included plain scan, hepatic arterial-dominant phase, and portal venous-dominant phase CT scans. Results showed that the Dice value of the proposed method was significantly higher than those of the full convolutional network and region-growing method. Then, 3D reconstruction and registration were performed on the segmentation results of the liver region of DCE-CT images. The proposed method obtained the best performance, which can provide technical support for the big data analysis of liver diseases.

CLASSIFICATION OF PROGRESSIVE STAGES OF ALZHEIMER’S DISEASE IN MRI HIPPOCAMPAL REGION

Alzheimer’s disease (AD) is a type of neuronal brain disorder that is degenerative and results in memory loss, skills and cognitive changes. The primary diagnostic tests for the disorder are defined to be total brain atrophy and hippocampal atrophy. Early diagnosis is significant and the design of automatic systems is necessary for this disorder. A potential biomarker for AD is described using a hippocampal magnetic resonance imaging volumetry system that possesses certain limitations. This paper aims to analyze the transition of stages from normal cognition to different forms that ultimately leads to Alzheimer’s disease. The magnetic resonance imaging (MRI) images of different stages are derived from the standard database for the segregation of hippocampal region. Later, the morphological and radiomic features are extracted from the hippocampal regions of different stages, since the hippocampus plays a major role in memory. Classification of extracted features was performed using machine learning algorithms like ensemble tree classifiers. The classification results based on performance parameters specify that the bagged tree classifier is more efficient. The 4-way classification has an accuracy of 95.6% indicating certain misclassification between the two classes MCI and PMCI. To categorize these two classes, a 2-way classification is described that has an accuracy of 98.6%. With these results, an effective method is defined for the analysis and identification of the different progressive stages of Alzheimer’s disease.

Convolutional neuronal networks combined with X-ray phase-contrast imaging for a fast and observer-independent discrimination of cartilage and liver diseases stages

We applied transfer learning using Convolutional Neuronal Networks to high resolution X-ray phase contrast computed tomography datasets and tested the potential of the systems to accurately classify Computed Tomography images of different stages of two diseases, i.e. osteoarthritis and liver fibrosis. The purpose is to identify a time-effective and observer-independent methodology to identify pathological conditions. Propagation-based X-ray phase contrast imaging WAS used with polychromatic X-rays to obtain a 3D visualization of 4 human cartilage plugs and 6 rat liver samples with a voxel size of 0.7 × 0.7 × 0.7 µm3 and 2.2 × 2.2 × 2.2 µm3, respectively. Images with a size of 224 × 224 pixels are used to train three pre-trained convolutional neuronal networks for data classification, which are the VGG16, the Inception V3, and the Xception networks. We evaluated the performance of the three systems in terms of classification accuracy and studied the effect of the variation of the number of inputs, training images and of iterations. The VGG16 network provides the highest classification accuracy when the training and the validation-test of the network are performed using data from the same samples for both the cartilage (99.8%) and the liver (95.5%) datasets. The Inception V3 and Xception networks achieve an accuracy of 84.7% (43.1%) and of 72.6% (53.7%), respectively, for the cartilage (liver) images. By using data from different samples for the training and validation-test processes, the Xception network provided the highest test accuracy for the cartilage dataset (75.7%), while for the liver dataset the VGG16 network gave the best results (75.4%). By using convolutional neuronal networks we show that it is possible to classify large datasets of biomedical images in less than 25 min on a 8 CPU processor machine providing a precise, robust, fast and observer-independent method for the discrimination/classification of different stages of osteoarthritis and liver diseases.

Experimental study on electrical characteristics of gassy coal during extrusion process in different stage

In this study, a stress-oriented experiment of gas-containing coal extrusion was performed by establishing an experimental system integrating gas injection, loading, and electrical testing. Then, the apparent resistivity images in different stages of gassy coal extrusion evolution were obtained. Finally, multi-parameter electrical characteristic parameters were extracted, and the variation and characterization significance of characteristic parameters were analyzed. The results show that the overall values of apparent resistivity images decrease in the gas adsorption equilibrium and stress loading stages. After the extrusion occurs, the values grow remarkably; in addition, there exist abnormal resistance values in some areas, which is consistent with the distribution of coal fractures. The fundamental reason for this phenomenon lies in the changed conductive channel within gassy coal. Moreover, average and maximum values of apparent resistivity both decrease first before they increase, whereas the current and spontaneous potential both rise first and then fall, of which the current changes more obviously. These changes, which characterize the evolution process of gassy coal extrusion, can provide theoretical guidance and experimental basis for geophysical exploration of gas dynamic disasters in coal and rock.

Study on value of ultrasonic elastography in diagnosis of clinical staging of cervical cancer and efficacy evaluation of radiotherapy.

The aim of this study was to investigate the application of ultrasonic elastography in the diagnosis of the clinical staging of cervical cancer (CC) and its evaluation value of the treatment effect of CC. A total of 160 suspected CC patients treated in our hospital from September 2016 to March 2018 were collected. Transvaginal conventional ultrasound and ultrasonic elastography were performed on patients to compare the results of the two in the diagnosis of the pathology and clinical staging of CC. Radiotherapy was used for patients confirmed as CC75 in 160 suspected CC patients. The value difference of strain ratio (SR) between conventional ultrasound and elastic ultrasound in the efficacy evaluation of CC patients was compared. The sensitivity (94.67%), specificity (92.94%) and diagnostic accordance rate (93.75%) of ultrasonic elastography for CC were significantly higher than those of conventional ultrasound, with a statistically significant difference (P<0.001). The sensitivity and diagnostic accordance rate of ultrasonic elastography for the pathological diagnosis of CC in stage III and IV were significantly higher than those of conventional ultrasound, with a statistically significant difference (P<0.05). The sensitivity, specificity and diagnostic accordance rate of elastic ultrasound SR value in the efficacy evaluation of radiotherapy in CC patients were higher than those of conventional ultrasound. Except for the specificity, the other two P-values were <0.05, with a statistically significant difference. The elastography images of different stages of CC have some characteristic features. Ultrasonic elastography has a certain clinical value for the diagnosis and efficacy evaluation of CC.

Range extension of Christisonia scortechinii from mainland Southeast Asia into Borneo, and notes on the distinction between Aeginetia and Christisonia (Orobanchaceae)

Background Christisonia is a little-documented and poorly studied root-parasitic genus in the Orobanchaceae occurring in India, China, Indochina and part of the Malesian region. Recent collection of a Christisonia taxon in Kinabalu Park in Sabah, Borneo, taxonomically identical to earlier Sabah collections that have hitherto not been recorded in the literature, led to an assessment of the taxonomic identity of the species against Christisonia scortechinii, C. siamensis, C. sinensis and related species.ResultsSome taxa in China, Indochina, the Malay Peninsula, and the Philippines are morphologically identical to the Borneo taxon except in the number of calyx lobes, but differ by several distinctive characters from other well-distinguished species in the region. Studies of dried herbarium specimens, augmented by photographic images of different stages of fresh flowering material and a scrutiny of available descriptions confirmed that the calyx has two primary lobes in the bud that may separate into 3–5 portions, giving a variable number of apparent lobes in specimen material collected at different localities. This new scrutiny of the calyx also permitted an improved description of the calyx differences that separate Christisonia and the closely related Aeginetia, which have not been clearly elucidated in the past.Conclusions Christisonia scortechinii Prain (Orobanchaceae), the only species that was described as having an initially spathaceous calyx among species of this root-parasitic genus, is newly recorded for Borneo (including Kinabalu Park, where its presence has been overlooked). The range of the species in mainland Southeast Asia, previously extended from Peninsular Malaysia to Thailand and Vietnam, is here further extended to Laos and China. Christisonia wightii Elmer (relevant to the Philippines) and C. sinensis Beck (China) are reduced to synonymy.

Macroscopic Analysis of Spray Development Using Direct Injection for Studying Ethanol Fuel Behavior

A great difficulty in spray analysis is the intrinsic subjectivity in the manual measurements of macroscopic spray characteristics. Within its contexts this work has the main objective to demonstrate a systematic methodology for the spray analysis adopted for acquiring the data results based on numerical criterion dealing with the numerical matrices that represent the spray images. The results shown in this work refers to EXXSOL D60 injection, a tested fluid used to simulate ethanol spray characteristics. The characteristics analyzed were spray penetration, spray pattern at various moments after start of injection and the total volume of the cone spray also as a function of time. The methodology applied uses the numerical matrices of images in different stages of injections. A computational routine written in Matlab environment deals with the numerical matrices of the spray images to localize the spray boundaries based on a numerical criterion. All the subsequent analysis is then performed with the boundaries location data in hand. The results show higher growth of penetration in the beginning of injections, higher displacements of the bottom part of the spray also in the beginning of injections and a linear growth of spray volume injected. The importance of all the results acquired in this work demonstrated that the proposed methodology is suitable for spray analysis.

Study of the termination phase of plasma production and the formation of magnetic flux breakthroughs during wire array implosion

The phenomenon of magnetic flux breakthrough into a wire array during its implosion was studied experimentally at the Angara-5-1 facility. It is shown that breakthroughs develop in the final stage of plasma production from the wire material and occur near the initial wire position. The spatial distributions of the azimuthal magnetic field within tungsten, molybdenum, copper, and aluminum wire arrays were studied using magnetic probes. The distributions of the azimuthal magnetic field B φ(z, t) along the array height in different stages of implosion were measured, and the characteristic dimensions of regions with a nonuniform magnetic field that appear during magnetic flux breakthroughs at the outer boundary of the wire array plasma were determined. The dimensions of these regions are compared with those of the regions with depressed plasma radiation observed in frame and time-integrated X-ray images. The dynamics of the distribution B φ(z, t) in regions with a nonuniform magnetic field during breakthroughs of the azimuthal magnetic flux is compared with that of the spatial distribution of pinch radiation in the frame X-ray images in different stages of implosion. The experimental data on the characteristics of spatially nonuniform breakthroughs of the magnetic flux into the wire array are analyzed using the plasma rainstorm model proposed by V.V. Aleksandrov et al. (JETP 97, 745 (2003)). The plasma density in the region of magnetic flux breakthrough is estimated.

High Quality Document Digitization Equipment

The paper describes an equipment specialized in digitization of single documents, journal-type documents and books. The equipment is designed and assembled at Politehnica University of Timisoara and works in a station developed within the European project thinkMOTION. The optical calculus aimed optimal illumination of two symmetrical areas and high quality of captured images. The object of scanning is printed matter, which exists exclusively in paper form and originates from different periods of scientific evolution. The mechanical design was based on criteria such as: flatness of active surfaces, quick placement and removal of the original document, mechanical raw focusing facilities, adjustment regarding the thickness of the original document and finding constructive solutions so that no damage is inflicted upon the original document, which may be one of a kind and, hence, historically very valuable. An original software was created in order to control the scanning process, to organize files and folders, which stock captured images in different stages of processing. The effective efficiency of the equipment is 10 12 pages/minute.

Anode Plasma Plume Development in a Vacuum Arc With a “Black-Body” Anode–Cathode Assembly

A new type of vacuum arc plasma source, the vacuum arc with a black body assembly (VABBA), was designed to produce a directed plasma jet. In the VABBA, cathode material is emitted into a closed vessel formed by the cathode and anode, re-evaporated from the anode, which is made from a refractory material, and heated by the arc, and a plasma jet is extracted through an aperture in the anode. Images of different stages of the jet development are presented.

REDUCCIÓN HIDROSTATICA DE INVAGINACIÓN INTESTINAL GUIADA POR ULTRASONIDO: UNA NUEVA OPCIÓN

Ileocolic intussusception is an important cause of acute abdomen in infants. When there is no surgical indication, reduction under fluorosco - pic vision has been the main radiologic treatment performed in our country. Ultrasound examination is broadly used as a diagnostic method but reports on local experiences with ultrasound for guidance in intussusception reduction have not been recorded. A series of five cases of successful hydrostatic reduction performed under ultrasonographic control is presen- ted and images of different stages of the reduction process are shown. Our aim is to promote a change in monitoring procedures so as to avoid the use of ionizing radiation.

Near Infrared Transillumination in Acute Maxillary Sinusitis: Theoretical Background – Clinical Application – Diagnostic Potential – Limitations

Summary Among the inflammatory diseases of the paranasal sinuses in man the acute maxillary sinusitis shows a particularily high incidence. Mostly emerging from a primarily viral rhinitis or rhinosinusitis the paranasal inflammation secondarily becomes purulent, if mucosal swellings and drainage disorders in the osteomeatal unit of the middle nasal meatus persist to be. The insufficient ventilation of the related paranasal sinuses – sinus maxillaris, sinus ethmoidalis and sinus frontalis – gives rise to a bacterial superinfection of the mucosa. In cases where the right diagnosis has not been found early enough or the acute sinusitis stays untreated the situation can culminate in serious complications to the orbit, to the facial soft tissues and even to the endocranium possibly leaving continual damages to the patient' health. Despite the otorhinolaryngologic examination significantly improved and refined by endo- and transnasal endoscopy, the direct visual inspection of the maxillary sinus for diagnostic reasons is normally not possible. This refers to the very small natural orifice of the maxillary sinus and the mucosal swellings which block the endoscope from penetrating into the middle nasal meatus as well as the sinus. Therefore plain film X-ray-imaging and sonography – in minor cases and in the follow up period – represent the gold standard for making the diagnosis of sinusitis up to now. Stimulated by promising basic investigations on the small spectrum light transillumination of biological tissues with selected wavelengths we re-adopted the principle of diaphanoscopy for diagnostic imaging of the maxillary sinuses. For its clinical application we designed a measuring setup where we replaced “cold (white) light transillumination” of the sinus by diaphanoscopy with photons of the near infra red spectrum of light (NIR). In this narrow part of the spectrum ranging from a wavelength of 650 to 1100 nm – the so-called ‘optical window’ – the incidence of photon scattering is much higher than absorption events by the tissue. This biophysical finding renders it possible in an excellent manner to utilize NIR-photons for the transillumination of body cavities and their detection in order to create a two-dimensional imaging. Our clinically controlled study supplied clearly categorizable NIR-diaphanoscopic images of different stages of an acute maxillary sinusitis showing a good positive correlation to traditional plain radiography and computer tomography (CT scan-imaging). Additionally NIR-diaphanoscopy is not only a system of morphological imaging but also of biomonitoring in the considered anatomical area.

Geomorphology of buried glacigenic horizons in the Barents Sea from three-dimensional seismic data

Abstract The glacigenic sequence of the southwestern Barents Sea shelf has for the first time been studied using 3-D seismic data. The close spacing of 3-D lines and powerful computer workstation interpretation techniques have allowed detailed mapping of the observed features. Several generations of subglacial lineations observed on four different palaeo-surfaces are interpreted to reflect the flow patterns of palaeo-ice sheets. To our knowledge, this is the first time that multiple levels of subglacial lineations have been observed. The lineations are 2.5–8 m in relief, 50 to 180 m wide and 0.5 to 20 km long. All four surfaces show a main lineation pattern comprising lineations with a N-S trend, suggesting that the dominant ice flow was directed northwards across the Barents Sea shelf at least four times during the last 0.8 Ma. Two of the surfaces display semi-circular to oblong depressions trending mainly in the same direction as the sub-parallel lineations. These depressions are 9–53 m in relief, 1.25–3.2 km wide and 1.9–9 km long. In contrast to the buried surfaces, the sea floor is dominated by 2.5–25 m deep cross-cutting iceberg plough-marks from the deglaciation phase of the last Barents Sea ice sheet. The 3-D seismic data are conventional industry data. Despite relatively low seismic frequencies and, hence, limited vertical resolution of seismic profiles, time slices and sub-horizontal time maps are of high spatial resolution, providing detailed images of different stages of buried Quaternary glacial geomorphology.