Image Recording Research Articles

Heterogeneous factors influence social cognition across diverse settings in brain health and age-related diseases

AbstractAging diminishes social cognition, and changes in this capacity can indicate brain diseases. However, the relative contribution of age, diagnosis and brain reserve to social cognition, especially among older adults and in global settings, remains unclear when considering other factors. Here, using a computational approach, we combined predictors of social cognition from a diverse sample of 1,063 older adults across nine countries. Emotion recognition, mentalizing and overall social cognition were predicted via support vector regressions from various factors, including diagnosis (subjective cognitive complaints, mild cognitive impairment, Alzheimer’s disease and behavioral variant frontotemporal dementia), demographics, cognition/executive function, brain reserve and motion artifacts from functional magnetic resonance imaging recordings. Higher cognitive/executive functions and education ranked among the top predictors, outweighing age, diagnosis and brain reserve. Network connectivity did not show predictive values. The results challenge traditional interpretations of age-related decline, patient–control differences and brain associations of social cognition, emphasizing the importance of heterogeneous factors.

Non-Cascaded and Crosstalk-Free Multi-Image Encryption Based on Optical Scanning Holography Using 2D Orthogonal Compressive Sensing.

We propose a non-cascaded and crosstalk-free multi-image encryption method based on optical scanning holography and 2D orthogonal compressive sensing. This approach enables the simultaneous recording and encryption of multiple plaintext images without mechanical scanning, while allows for independent retrieval of each image with exceptional quality and no crosstalk. Two features would bring about more substantial security and privacy. The one is that, by employing a sequence of pre-designed structural patterns as encryption keys at the pupil, multiple samplings can be achieved and ultimately the holographic cyphertext can be obtained. These patterns are generated using a measurement matrix processed with the generalized orthogonal one. As a result, one can accomplish the differentiation of images prior to the recording and thus neither need to pretreat the pending images nor to suppress the out-of-focus noise in the decrypted image. The other one is that, the non-cascaded architecture ensures that different plaintexts do not share sub-keys. Meanwhile, compared to 1D orthogonal compressive sensing, the 2D counterpart makes the proposed method to synchronously deal with multiple images of more complexity, while acquire significantly high-quality decrypted images and far greater encryption capacity. Further, the regularities of conversion between 1D and 2D orthogonal compressive sensing are identified, which may be instructive when to manufacture a practical multi-image cryptosystem or a single-pixel imaging equipment. A more general method or concept named synthesis pupil encoding is advanced. It may provide an effective way to combine multiple encryption methods together into a non-cascaded one. Our method possesses nonlinearity and it is also promising in multi-image asymmetric or public key cryptosystem as well as multi-user multiplexing.

20-HETE mediated TRPV1 activation drives allokinesis via MrgprA3+ neurons in chronic dermatitis.

Rationale: Noxious stimuli are often perceived as itchy in patients with chronic dermatitis (CD); however, itch and pain mechanisms of CD are not known. Methods: TRPV1 involvement in CD was analyzed using a SADBE induced CD-like mouse model, and several loss- and gain-of-function mouse models. Trigeminal TRPV1 channel and MrgprA3+ neuron functions were analyzed by calcium imaging and whole-cell patch-clamp recordings. Lesional CD-like skin from mice were analyzed by unbiased metabolomic analysis. 20-HETE availability in human and mouse skin were determined by LC/MS and ELISA. And finally, HET0016, a selective 20-HETE synthase inhibitor, was used to evaluate if blocking skin TRPV1 activation alleviates CD-associated chronic itch or pain. Results: While normally a pain inducing chemical, capsaicin induced both itch and pain in mice with CD condition. DREADD silencing of MrgprA3+ primary sensory neurons in these mice selectively decreased capsaicin induced scratching, but not pain-related wiping behavior. In the mice with CD condition, MrgprA3+ neurons showed elevated ERK phosphorylation. Further experiments showed that MrgprA3+ neurons from MrgprA3;Braf mice, which have constitutively active BRAF in MrgprA3+ neurons, were significantly more excitable and responded more strongly to capsaicin. Importantly, capsaicin induced both itch and pain in MrgprA3;Braf mice in an MrgprA3+ neuron dependent manner. Finally, the arachidonic acid metabolite 20-HETE, which can activate TRPV1, was significantly elevated in the lesional skin of mice and patients with CD. Treatment with the selective 20-HETE synthase inhibitor HET0016 alleviated itch in mice with CD condition. Conclusion: Our results demonstrate that 20-HETE activates TRPV1 channels on sensitized MrgprA3+ neurons, and induces allokinesis in lesional CD skin. Blockade of 20-HETE synthesis or silencing of TRPV1-MrgprA3+ neuron signaling offers promising therapeutic strategies for alleviating CD-associated chronic itch.

PointMCD: Boosting Deep Point Cloud Encoders Via Multi-View Cross-Modal Distillation for 3D Shape Recognition

As two fundamental representation modalities of 3D objects, 3D point clouds and multi-view 2D images record shape information from different domains of geometric structures and visual appearances. In the current deep learning era, remarkable progress in processing such two data modalities has been achieved through respectively customizing compatible 3D and 2D network architectures. However, unlike multi-view image-based 2D visual modeling paradigms, which have shown leading performance in several common 3D shape recognition benchmarks, point cloud-based 3D geometric modeling paradigms are still highly limited by insufficient learning capacity due to the difficulty of extracting discriminative features from irregular geometric signals. In this article, we explore the possibility of boosting deep 3D point cloud encoders by transferring visual knowledge extracted from deep 2D image encoders under a standard teacher-student distillation workflow. Generally, we propose PointMCD, a unified multi-view cross-modal distillation architecture, including a pretrained deep image encoder as the teacher and a deep point encoder as the student. To perform heterogeneous feature alignment between 2D visual and 3D geometric domains, we further investigate visibility-aware feature projection (VAFP), by which point-wise embeddings are reasonably aggregated into view-specific geometric descriptors. By pair-wisely aligning multi-view visual and geometric descriptors, we can obtain more powerful deep point encoders without exhausting and complicated network modification. Experiments on 3D shape classification, part segmentation, and unsupervised learning strongly validate the effectiveness of our method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The code and data will be publicly available at</i> <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/keeganhk/PointMCD</uri> .

Evaluation of Fine Needle Aspiration Cytology [Bethesda Classification] Versus Ultrasonography [Thyroid imaging recording and data system [TIRADS] Classification] in Diagnosis of Thyroid Nodule

Evaluation of Fine Needle Aspiration Cytology [Bethesda Classification] Versus Ultrasonography [Thyroid imaging recording and data system [TIRADS] Classification] in Diagnosis of Thyroid Nodule

Research on Digital Image Record in Intangible Cultural Heritage Inheritance Innovation under the Background of Big Data

Abstract The purpose of this paper is to investigate the digital lens presentation effect and image dissemination effect of intangible cultural heritage. In order to test the lens boundary detection technology of ICH digital images, we focus on analyzing the number of image frames, the number of mutations and the number of gradual changes of ICH characters, space-time and events, and exploring the checking completeness, the checking accuracy and the comprehensive detection rate of this paper’s algorithm and the dual-threshold comparative method on different types of ICH image fragments. Combined with the descriptive analysis of valid samples, we explore the main types of transmission of NRM digital images and clarify the degree of media utilization and the ranking of transmission power of NRM digital images in the Yangtze River Delta region. Shanghai has the strongest online dissemination power of traditional theater, traditional fine arts and traditional arts and crafts, with 1284586, 310468, and 237818, respectively, while traditional music, Chinese opera and folklore have the weakest dissemination power in Shanghai. Traditional music makes up 18.73% of them. To ensure non-heritage culture’s inheritance, it is necessary to strengthen the use of digital imaging technology to achieve linkage communication between non-heritage cultures and build an overall communication system.

Analysis of cellular response to drugs with a microfluidic single-cell platform based on hyperspectral imaging

BackgroundCellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics examination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co-culture with drugs, which are relatively complex and time-consuming. Moreover, these methods can only indicate the drug effectiveness on cell colony rather than single cells. Thus, to meet the requirements of personal precision medicine, the development of drug response analysis on the high resolution of single cell is demanded. ResultsTo provide precise result for drug response on single-cell level, a microfluidic platform coupled with the label-free hyperspectral imaging was developed. With the help of horizontal single-cell trapping sieves, hundreds of single cells were trapped independently in microfluidic channels for the purposes of real-time drug delivery and single-cell hyperspectral image recording. To significantly identify the cellular hyperspectral change after drug stimulation, the differenced single-cell spectrum was proposed. Compared with the deep learning classification method based on hyperspectral images, an optimal performance can be achieved by the classification strategy based on differenced spectra. And the cellular response to different reagents, for example, K+, Epidermal Growth Factor (EGF), and Gefitinib at different concentrations can be accurately characterized by the differenced single-cell spectra analysis. Significance and noveltyThe high-throughput, rapid analysis of cellular response to drugs at the single-cell level can be accurately performed by our platform. After systematically analyzing the materials and the structures of the single-cell microfluidic chip, the optimal single-cell trapping method was proposed to contribute to the further application of hyperspectral imaging on microfluidic single-cell analysis. And the hyperspectral characterization of single-cell with cancer drug stimulation proved the application potential of our method in personal cancer medication.

Causal functional connectivity in Alzheimer's disease computed from time series fMRI data.

Functional connectivity between brain regions is known to be altered in Alzheimer's disease and promises to be a biomarker for early diagnosis. Several approaches for functional connectivity obtain an un-directed network representing stochastic associations (correlations) between brain regions. However, association does not necessarily imply causation. In contrast, Causal Functional Connectivity (CFC) is more informative, providing a directed network representing causal relationships between brain regions. In this paper, we obtained the causal functional connectome for the whole brain from resting-state functional magnetic resonance imaging (rs-fMRI) recordings of subjects from three clinical groups: cognitively normal, mild cognitive impairment, and Alzheimer's disease. We applied the recently developed Time-aware PC (TPC) algorithm to infer the causal functional connectome for the whole brain. TPC supports model-free estimation of whole brain CFC based on directed graphical modeling in a time series setting. We compared the CFC outcome of TPC with that of other related approaches in the literature. Then, we used the CFC outcomes of TPC and performed an exploratory analysis of the difference in strengths of CFC edges between Alzheimer's and cognitively normal groups, based on edge-wise p-values obtained by Welch's t-test. The brain regions thus identified are found to be in agreement with literature on brain regions impacted by Alzheimer's disease, published by researchers from clinical/medical institutions.

Borneol exerts its antipruritic effects by inhibiting TRPA1 and activating TRPM8

Ethnopharmacological relevanceBorneol is a long-established traditional Chinese medicine that has been found to be effective in treating pain and itchy skin. However, whether borneol has a therapeutic effect on chronic itch and its related mechanisms remain unclear. Aim of the studyTo investigate the antipruritic effect of borneol and its molecular mechanism. Materials and methodsDrugBAN framework and molecular docking were applied to predict the targets of borneol, and the calcium imaging or patch-clamp recording analysis were used to detect the effects of borneol on TRPA1, TRPM8 or TRPV3 channels in HEK293T cells. In addition, various mouse models of acute itch and chronic itch were established to evaluate the antipruritic effects of borneol on C57BL/6J mice. Then, the borneol-induced pruritic relief was further investigated in Trpa1−/−, Trpm8−/−, or Trpa1−/−/Trpm8−/− mice. The effects of borneol on the activation of TRPM8 and the inhibition of TRPA1 were also measured in dorsal root ganglia neurons of wild-type (WT), Trpm8−/− and Trpv1−/− mice. Lastly, a randomized, double-blind study of adult patients was conducted to evaluate the clinical antipruritic effect of borneol. ResultsTRPA1, TRPV3 and TRPM8 are the potential targets of borneol according to the results of DrugBAN algorithm and molecular docking. Calcium imaging and patch-clamp recording analysis demonstrated that borneol activates TRPM8 channel-induced cell excitability and inhibits TRPA1 channel-mediated cell excitability in transfected HEK293T cells. Animal behavior analysis showed that borneol can significantly reduce acute and chronic itch behavior in C57BL/6J mice, but this effect was eliminated in Trpa1−/−, Trpm8−/− mice, or at least in Trpa1−/−/Trpm8−/− mice. Borneol elicits TRPM8 channel induced [Ca2+]i responses but inhibits AITC or SADBE-induced activation of TRPA1 channels in dorsal root ganglia neurons of WT and Trpv1−/− mice, respectively. Furthermore, the clinical results indicated that borneol could reduce itching symptoms in patients and its efficacy is similar to that of menthol. ConclusionBorneol has therapeutic effects on multiple pruritus models in mice and patients with chronic itch, and the mechanism may be through inhibiting TRPA1 and activating TRPM8.

Digital Content Management in the Age of Digital Transformation

Digital Content is a new Phenomenon in the Contemporary Net world. It includes a number of activities in the form of text files, editing, imaging, animations, graphics, documents, and audio-video recordings as well as safe custodian for users. The files or documents can easily be managed and transformed with the help of Digital Content quickly. This paper will try to cover a wide and variety of elements in the manner of background, introduction and discussion of the main theme of digital content management as well as the elements related with digital transformation. Besides, the definitions and role of libraries in digital content management system will also be discussed. In our contemporary day to day livelihood, A lot of people read a lot of digital material every day by reading news stories, papers, blogs, digital mags, watching videos on Google or YouTube, and sending notes to friends and family. Advertisements, Cinema and entertainment sites are also watched and enjoyed by a sizeable number of people. All these activities fall within the management of digital content which needs to be very attractive and meaningful in a short and brief manner. Thus the topic as mentioned above, needs to explore with modern outlook.

Functional engineering of human iPSC-derived parasympathetic neurons enhances responsiveness to gastrointestinal hormones.

Food-derived biological signals are transmitted to the brain via peripheral nerves through the paracrine activity of gastrointestinal (GI) hormones. The signal transduction circuit of the brain-gut axis has been analyzed in animals; however, species-related differences and animal welfare concerns necessitate investigation using in vitro human experimental models. Here, we focused on the receptors of five GI hormones (CCK, GLP1, GLP2, PYY, and serotonin (5-HT)), and established human induced pluripotent stem cell (iPSC) lines that functionally expressed each receptor. Compared to the original iPSCs, iPSCs expressing one of the receptors did not show any differences in global mRNA expression, genomic stability, or differentiation capacities of the three germ layers. We induced parasympathetic neurons from these established iPSC lines to assess vagus nerve activity. We generated GI hormone receptor-expressing neurons (CCKAR, GLP1R, and NPY2R-neuron) and tested their responsiveness to each ligand using Ca2+ imaging and microelectrode array recording. GI hormone receptor-expressing neurons (GLP2R and HTR3A) were generated directly by gene induction into iPSC-derived peripheral nerve progenitors. These receptor-expressing neurons promise to contribute to a better understanding of how the body responds to GI hormones via the brain-gut axis, aid in drug development, and offer an alternative to animal studies.

Variable selection for nonlinear dimensionality reduction of biological datasets through bootstrapping of correlation networks

Identifying the most relevant variables or features in massive datasets for dimensionality reduction can lead to improved and more informative display, faster computation times, and more explainable models of complex systems. Despite significant advances and available algorithms, this task generally remains challenging, especially in unsupervised settings. In this work, we propose a method that constructs correlation networks using all intervening variables and then selects the most informative ones based on network bootstrapping. The method can be applied in both supervised and unsupervised scenarios. We demonstrate its functionality by applying Uniform Manifold Approximation and Projection for dimensionality reduction to several high-dimensional biological datasets, derived from 4D live imaging recordings of hundreds of morpho-kinetic variables, describing the dynamics of thousands of individual leukocytes at sites of prominent inflammation. We compare our method with other standard ones in the field, such as Principal Component Analysis and Elastic Net, showing that it outperforms them. The proposed method can be employed in a wide range of applications, encompassing data analysis and machine learning.

A Study of Clinical Profile, Radiological and Electroencephalographic Characteristics of Sporadic Creutzfeldt-Jakob Disease From a Tertiary Care Hospital.

Background Sporadic Creutzfeldt-Jakob disease (CJD), the most common form of human prion disease, is the archetypal diagnosis in this category. However, the spectrum of possible diagnoses is wide, encompassing various treatable conditions. A lack of standardized diagnostic criteria and a tendency to opt for brain biopsies and clinical autopsies can be limiting factors in reaching a conclusive diagnosis. Objective This study aims to retrospectively analyze clinical and investigative findings in patients referred to a specialized neurology clinic exhibiting rapidly progressive dementia. These patients were ultimately diagnosed with Probable sporadic Creutzfeldt-Jakob disease (CJD) based on the 2018 CDC criteria for sporadic CJD. Materials and Methods This study included cases of CJD diagnosed based on clinical, electrophysiological, and imaging parameters at a tertiary care hospital in India from 2016 to 2020. The diagnostic criteria proposed by the CDC (Centers for Disease Control and Prevention) were employed to categorize patients as definite, probable, or possible CJD cases. All patients underwent MRI (magnetic resonance imaging) imaging and EEG ( electroencephalography) recording, while diagnostic brain biopsies were not conducted due to a lack of consent from close relatives. Results This observational descriptive study comprised four patients diagnosed with Probable sporadic CJD (sCJD), all of whom were female. The patients exhibited an age range of 57 to 75 years at the onset of the disease, with a mean age of onset at 67.5 years. Unfortunately, all patients succumbed to the disease within 6 months of its onset. Rapidly progressive dementia was a common symptom in all cases. Additionally, patient one and patient four displayed myoclonus and dystonia, patient two exhibited myoclonus and akinetic mutism, and patient three had myoclonus, chorea, and ataxia. MR brain imaging, including T2 sequence, FLAIR sequence, and DWI/ADC mapping, was performed on all patients, revealing both cortical gray matter and deep gray matter (basal ganglia) T2/FLAIR hyperintensities with DWI restriction. A cortical ribboning pattern was observed in all cases. EEG results indicated generalized delta slow waves with triphasic complexes in three patients, while patient three alone displayed periodic sharp wave complexes at a frequency of 1 per 1 - 1.5 seconds. Conclusion MRI with DWI and ADC brain mapping emerges as the most valuable diagnostic tool for patients with clinical presentations suggesting sCJD. In this study, all patients displayed restricted diffusion, as confirmed by ADC mapping. Regrettably, the characteristic features of sCJD with restricted diffusion in the cortex, thalamus, and basal ganglia may often elude detection by radiologists outside specialized centers, resulting in diagnostic delays. Conversely, when basal ganglia or cortical signal abnormalities are detected in conjunction with parenchymal swelling, alternative diagnoses such as encephalitis or lymphoma should be considered, as parenchymal swelling is not a typical feature of sCJD as revealed by MRI.

A new process for recording minute disturbances to a crystal

We found a process for recording minute disturbances to a crystal that does not involve deposition of energy. It depends on the crystal entering an unstable state during cooling after growth that causes an exothermic phase-change in the crystal when triggered by a transient disturbance to the lattice. Using this recording process, a search for rare events of cosmological origin in 0.3 m3 of mica was made. One was a very high energy event of unknown origin or cause. Adoption of digital recording of images and machine analysis would facilitate searches for evidence of dark matter. Although this recording process cannot be replicated in a laboratory, it is far more sensitive than the etch-track technique. It offers an alternative method to photo-emission for seeking evidence of dark matter. As the crystals of muscovite are mined commercially, they are readily available.

Early Detection of Forest and Land Fires Using Hotspots Data from S-NPP VIIRS Satellite Imagery Recording in the New Capital City Location

Forest and land fires are a natural disaster whose frequency is increasing annually, especially during dry season, forest and land fires also impact the new capital city in East Kalimantan as well. Early detection is very critical to prevent increasing impact of forest and land fires. Early detection can be done using hotspot data from satellite image recording. Based on this, it is very necessary to conduct research entitled Early Detection of Forest and Land Fires Using Hot Spots from “S-NPP VIIRS Image Records in the New Capital City Location”. The research was conducted in the new capital city location in East Kalimantan Province which consists of several sub-districts and 10 districts / cities. Descriptive quantitative method is used to analysed secondary data consist of hotspot data in each sub-district from satellite imagery data record namely S-NPP VIIRS from 2012-2022. Population number is same as the number of samples, namely hotspots number in each sub-district. Descriptive geostatistical analysis technique in ArcGIS software is used to process hotspot data. It is known that from 2012-2022, Kutai Kartanegara has the highest hotspots number with 38,694 spots, it followed by East Kutai with 36,915 spots, both are viewed from district/city scope. When viewed on the district scope, the highest was in Bengalon district from East Kutai District with 9,027 spots, it followed by Muarakaman District from Kutai Kartanagara District with 7,713 spots. The number of hotspots varies quite a lot amongst sub-district in the new capital city location, whose each have a numerous number that needs serious attention in order to minimize the loss of life and property. From analysis above, early detection is very important as a form of early warning system.

The advantages of general anesthesia subthalamic deep brain stimulation for Parkinson's disease in the enhanced recovery after surgery: A randomized clinical trial.

With advancements in imaging and microelectrode recording techniques, general anesthesia (GA) has emerged as an alternative option for Parkinson's disease (PD) patients undergoing subthalamic nucleus deep brain stimulation (STN-DBS). In this study, we compared the advantages and disadvantages of using GA and local anesthesia for STN-DBS in enhanced recovery after surgery (ERAS). Surgical outcomes of STN-DBS were evaluated using the unified PD rating scales (UPDRS). CT and magnetic resonance imaging scans are used to evaluate intracranial conditions. State-trait anxiety inventory and hospital anxiety and depression scale are used to evaluate patients' perioperative psychology. Anesthesia method does not significantly impact the accuracy of microelectrode placement or the improvement of postoperative symptoms. However, the local anesthesia group had a higher incidence of intracranial air, as well as higher rates of postoperative complications such as headache, dizziness, vomiting, and delirium. GA effectively alleviated preoperative anxiety and resulted in lower levels of perioperative anxiety and psychological stress compared to local anesthesia. Additionally, the GA group had shorter surgery duration, earlier ambulation, and a shorter average hospital stay. DBS under GA is safe and effective. Due to shorter surgical duration, reduced occurrence of perioperative complications, effective reduction of preoperative anxiety, and faster postoperative recovery, DBS under GA is better aligned with the concept of ERAS.

Dynamic changes of vocal tract dimensions with sound pressure level during messa di vocea).

The messa di voce (MdV), which consists of a continuous crescendo and subsequent decrescendo on one pitch is one of the more difficult exercises of the technical repertoire of Western classical singing. With rising lung pressure, regulatory adjustments both on the level of the glottis and the vocal tract are required to keep the pitch stable. The dynamic changes of vocal tract dimensions with the bidirectional variation of sound pressure level (SPL) during MdV were analyzed by two-dimensional real-time magnetic resonance imaging (25 frames/s) and synchronous audio recordings in 12 professional singer subjects. Close associations in the respective articulatory kinetics were found between SPL and lip opening, jaw opening, pharynx width, uvula elevation, and vertical larynx position. However, changes in vocal tract dimensions during plateaus of SPL suggest that perceived loudness could have been varied beyond the dimension of SPL. Further multimodal investigation, including the analysis of sound spectra, is needed for a better understanding of the role of vocal tract resonances in the control of vocal loudness in human phonation.

Small-Sized Hyperspectrometers with On-Line Image Recording

Small-Sized Hyperspectrometers with On-Line Image Recording

Hotspot Distribution Analysis as Forest and Land Fire Indicators in the New National Capital City (IKN)

East Kalimantan Province is planned as the new national capital city (IKN). Forest and land fires occur regularly every year and their frequency is increasing, especially during the dry season. This research uses secondary data, namely hotspot data. Hotspot data was obtained from the results of the 2012-2022 S-NPP VIIRS image recording. Data analysis in this study used descriptive and statistical analysis. The results of processing and analysis of the distribution of hotspots are overlaid with administrative maps so that the distribution of hotspots in each district in the study area can be identified. The results of the study show that hotspots distribution from the 2012-2022 S-NPP VIIRS image recording in East Kalimantan Province is varies quite a bit in each district. The highest hotspots distribution is in Kutai Kartanegara Regency and the lowest is in Mahakam Ulu and Penajam Paser Utara Regency. The higher number of hotspots is the higher incidence for forest and land fires. The distribution of hotspots needs to be known because it can be a form of early detection and fire mitigation so that the negative impact of fires can be minimized.

Determining the orientation of circular areas in video images

One of the ways to describe objects in images is to identify some of their characteristic points, or points of attention. The neighborhoods of attention points are described by descriptors (sets of features) in such way that they can be identified and compared. Based on these features, the search for identical points on other images is carried out. The feature selection process should take into account not only the position of the focus point, but also the size and possible shape of the local neighborhood. Different methods of finding identical characteristic points are known, which use rectangular or circular neighborhood to describe them. The rectangular windows used for neighborhood analysis do not allow selecting the same areas on the reference image and image which is rotated and analyzed. Round windows allow this. The article proposes and studies algorithms for determining the orientation of circular areas in video images, which makes it possible to calculate, in addition to invariant characteristics, characteristics that take into account the location of individual sections of such areas. These are the algorithms: • determination of the orientation of the circular area by moments of the first and second order; • calculation of the mutual orientation of the investigated circular area and the standard according to the moments of the first and second order. As a result of research and experiments, it was established that depending on the algorithm and the content of the circular areas, there are possible deviations in determining their orientation directions. Factors affecting this: accuracy of finding characteristic points; application of certain orientation determination algorithms; differences in the angle of video recording of the reference image and the image under investigation; the location of characteristic points, inside the object or on its border, especially when the background changes; size of neighborhood (analysis window) of characteristic points. It seems appropriate to continue the research orientation determination accuracy of circular areas by various algorithms. To reduce the influence of various side factors, artificial rather than real images should be studied