MOVING OBJECT TRACKING IN DYNAMIC IMAGE SEQUENCE BASED ON ESTIMATION OF MOTION VECTORS OF FEATURE POINTS

An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.

A framework of region-based dynamic image fusion

A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

Discrete-Time Dynamic Image Segmentation Using Oscillators with Adaptive Coupling

In this study, we propose a novel discrete-time coupled model to generate oscillatory responses via periodic points with a high periodic order. Our coupled system comprises one-dimensional oscillators based on the Rulkov map and a single globally coupled oscillator. Because the waveform of a one-dimensional oscillator has sharply defined peaks, the coupled system can be applied to dynamic image segmentation. Our proposed system iteratively transforms the coupling of each oscillator based on an input value that corresponds to the pixel value of an input image. This approach enables our system to segment image regions in which pixel values gradually change with respect to a connected region. We conducted a bifurcation analysis of a single oscillator and a three-coupled model. Through simulations, we demonstrated that our system works well for gray-level images with three isolated image regions.

Fabric Wetting and Wicking Measurement Based on Dynamic Image Acquisition and Processing

After a brief review of existing methods for fabric wetting and wicking measurement,a new numerical approach based on dynamic image acquisition and analysis was proposed to study the liquid wetting and wicking properties of woven fabrics.A measuring system was first developed to record on-site the images of liquid ascending in fabrics for a certain period of time.The hardware and software platforms and the experimental methods were described,and the image processing and analysis as well as other related algorithms were discussed in detail.The liquid front curves and rising rates in wetting and wicking were eventually obtained towards different fabrics.From liquid wicking curves,relationship between liquid ascending height and liquid ascending time agrees well with the Washburn theory.The data comparison between the numerical measurement and the traditional test proves the reliability of the numerical results.

Application of dynamic image analysis to the optical characterisation of fibrous bulk material

Dynamic image analysis provides an automated evaluation method to determine the size and shape of multiple particles. This method represents a common application for ordinary bulk material. The latest draft of ISO 13322–2:2021 describes the state of the art, but lacks instructions for handling fibrous bulk material. Interlocking fibres complicate the measurement conditions and require a disentanglement of fibrous samples during a pre-dispersion step. A further error source includes the fibre orientation inside the measurement zone of the device. If the thresholding algorithm fails to differentiate between the fibre projection area and the background, a subsequent image optimisation solves the problem. This article addresses the mentioned problems by analysing cotton cellulose and polyacrylonitrile fibres. Besides the execution of a pre-dispersion step, the experiments compare the discrepancies between dry and wet dispersion. Here, the software packages PAQXOS and ImageJ perform the image evaluation. In this case, the wet dispersion setup with a subsequent image evaluation by ImageJ provides comprehensible results.

Emotionally Resonant Branding: The Role of AI in Synthesising Dynamic Brand Images for Artists in the Music Industry

Artificial Intelligence (AI) expands its recognition rapidly through the past few years in the context of generating content dynamically, remarkably challenging the human creativity. This study aims to evaluate the efficacy of AI in enhancing personal branding for musicians, particularly in crafting brand images based on emotions received from the artist’s music will improve the audience perceptions regarding the artist’s brand. Study used a quantitative approach for the research, gathering primary data from the survey of 191 people—music lovers, musicians and music producers. The survey focuses on preferences, perceptions, and behaviours related to music consumption and artist branding. The study results demonstrate the awareness and understanding of AI’s role in personal branding within the music industry. Also, results indicate that such an adaptive approach enhances audience perceptions of the artist and strengthens emotional connections. Furthermore, over 50% of the participants indicated a desire to attend live events where an artist’s brand image adapts dynamically to their emotions. The study focuses on novel approaches in personal branding based on the interaction of AI-driven emotional data. In contrast to traditional branding concepts, this study indicates that AI can suggest dynamic and emotionally resonant brand identities for artists. The real time audience response gives proper guidance for the decision-making. This study enriches the knowledge of AI’s applicability to branding processes in the context of the music industry and opens the possibilities for additional advancements in building emotionally appealing brand identities.

Dynamic Visual Image Modeling Based on Mobile RobotSelf- Organizing Network in Internetof Things Perception Layer

The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.

In situ nanobubble sizing by visualization particle tracking and image-based dynamic light scattering

A novel method combining visualization particle tracking with image-based dynamic light scattering was developed to achieve the in situ and real-time size measurement of nanobubbles(NBs).First,the in situ size distribution of NBs was visualized by dark-field microscopy.Then,real-time size during the preparation was measured using image-based dynamic light scattering,and the longitudinal size distribution of NBs in the sample cell was obtained in a steady state.Results show that this strategy can provide a detailed and accurate size of bubbles in the whole sample compared with the commercial ZetaSizer Nano equipment.Therefore,the developed method is a real-time and simple technology with excellent accuracy,providing new insights into the accurate measurement of the size distribution of NBs or nanoparticles in solution.

Distortion-Free Data Embedding Scheme for High Dynamic Range Images

Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range （HDR） images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et aL＇s scheme in regard to the embedding rate——an average embedding rate of 0.1355 bpp compared with Yn et aL＇s scheme （0.1270 bpp）.

Shape recovery using high dynamic range images

An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.

An approach on dynamic earthquake prediction by georesistivitymeasurements

Experiences on earthquake prediction accumulated by the Chinese scientists in the last 20 years were synthetically analyzed. A prediction program was set up to demonstrate the development of the georesistivity anomaly by using of the dynamic image, accordingly the earthquake prone area can be recognized. By revising the DYBS Ⅰ, which was developed in 1989, and adding some latest achievements, we worked out a software on earthquake prediction by the geoelectric method the DYBS Ⅱ. Some new feature of DYBS Ⅱ are: the anomalous area may be determined by the space distribution and its time variation of geoelectric parameters; The dynamic process that is associated with the development of earthquake anomaly can be displayed on the computer screen; Technique for the prediction of an impending earthquake was included too. Some results of the Tangshan earthquake were presented at the end of this paper.

Pancreatic carcinoma coexisting with chronic pancreatitis versus tumor-forming pancreatitis:Diagnostic utility of the time-signal intensity curve from dynamic contrast-enhanced MR imaging

AIM: To evaluate the ability of the time-signal intensity curve (TIC) of the pancreas obtained from dynamic contrast-enhanced magnetic resonance imaging (MRI) for differentiation of focal pancreatic masses, especially pancreatic carcinoma coexisting with chronic pancreatitis and tumor-forming pancreatitis. METHODS: Forty-eight consecutive patients who underwent surgery for a focal pancreatic mass, including pancreatic ductal carcinoma (n = 33), tumor-forming pancreatitis (n = 8), and islet cell tumor (n = 7), were reviewed. Five pancreatic carcinomas coexisted with longstanding chronic pancreatitis. The pancreatic TICs were obtained from the pancreatic mass and the pancreatic parenchyma both proximal and distal to the mass lesion in each patient, prior to surgery, and were classified into 4 types according to the time to a peak: 25 s and 1, 2, and 3 min after the bolus injection of contrast material, namely, type-Ⅰ, Ⅱ, Ⅲ, and Ⅳ, respectively, and were then compared to the corresponding histological pancreatic conditions. RESULTS: Pancreatic carcinomas demonstrated type-Ⅲ (n = 13) or Ⅳ (n = 20) TIC. Tumor-forming pancreatitis showed type-Ⅱ (n = 5) or Ⅲ (n = 3) TIC. All islet cell tumors revealed type-Ⅰ. The type-Ⅳ TIC was only recognized in pancreatic carcinoma, and the TIC of carcinoma always depicted the slowest rise to a peak among the 3 pancreatic TICs measured in each patient, even in patients with chronic pancreatitis.CONCLUSION: Pancreatic TIC from dynamic MRI provides reliable information for distinguishing pancreatic carcinoma from other pancreatic masses, and may enable us to avoid unnecessary pancreatic surgery and delays in making a correct diagnosis of pancreatic carcinoma, especially, in patients with longstanding chronic pancreatitis.

Dynamic imaging of metallic contamination plume based on self-potential data

A dynamic imaging method for monitoring self-potential data was proposed.Based on the Darcy’s law and Archie’sformulas,a dynamic model was built as a state model to simulate the transportation of metallic ions in porous medium,and theNernst equation was used to calculate the redox potential of metallic ions for observation modeling.Then,the state model andobservation model form an extended Kalman filter cycle to perform dynamic imaging.The noise added synthetic data imaging testshows that the extended Kalman filter can effectively fuse the model evolution and observed self-potential data.The further sandboxmonitoring experiment also demonstrates that the self-potential can be used to monitor the activities of metallic ions and exactlyretrieve the dynamic process of metallic contamination.

DCE-MRI in hepatocellular carcinoma-clinical and therapeutic image biomarker

Dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)enables tumor vascular physiology to be assessed.Within the tumor tissue,contrast agents(gadolinium chelates)extravasate from intravascular into the extravascular extracellular space(EES),which results in a signal increase on T1-weighted MRI.The rate of contrast agents extravasation to EES in the tumor tissue is determined by vessel leakiness and blood flow.Thus,the signal measured on DCE-MRI represents a combination of permeability and perfusion.The semi-quantitative analysis is based on the calculation of heuristic parameters that can be extracted from signal intensity-time curves.These enhancing curves can also be deconvoluted by mathematical modeling to extract quantitative parameters that may reflect tumor perfusion,vascular volume,vessel permeability and angiogenesis.Because hepatocellular carcinoma(HCC)is a hypervascular tumor,many emerging therapies focused on the inhibition of angiogenesis.DCE-MRI combined with a pharmacokinetic model allows us to produce highly reproducible and reliable parametric maps of quantitative parameters in HCC.Successful therapies change quantitative parameters of DCE-MRI,which may be used as early indicators of tumor response to anti-angiogenesis agents that modulate tumor vasculature.In the setting of clinical trials,DCE-MRI may provide relevant clinical information on the pharmacodynamic and biologic effects of novel drugs,monitor treatment response and predict survival outcome in HCC patients.

Discrimination of Metastatic from Non-metastatic Mesorectal Lymph Nodes in Rectal Cancer Using Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Preoperative detection of lymph nodes（LNs） metastasis is always highly challenging for radiologists nowadays. The utility of quantitative dynamic contrast-enhanced magnetic resonance imaging（QDCE-MRI） in identifying LNs metastasis is not well understood. In the present study, 59 patients with histologically proven rectal carcinoma underwent preoperative QDCE-MRI. The short axis diameter ratio, long axis diameter ratio, short-to-long axis diameter ratio and QDEC-MRI parameters（Ktrans, Kep, fPV and Ve） values were compared between the non-metastatic（n=44） and metastatic（n=35） LNs groups based on pathological examination. Compared with the non-metastatic group, the metastatic group exhibited significantly higher short axis diameter（7.558±0.668 mm vs. 5.427±0.285 mm）, Ktrans（0.483±0.198 min-1 vs. 0.218±0.116 min^-1） and Ve（0.399±0.118 vs. 0.203±0.096） values（all P〈0.05）. The short-to-long axis diameter ratio, long axis diameter ratio, Kep and fPV values did not show significant differences between the two groups. In conclusion, our results showed that for LNs larger than 5 mm in rectal cancer, there are distinctive differences in the Ktrans and Ve values between the metastatic and non-metastatic LNs, suggesting that QDCE-MRI may be potentially helpful in identifying LNs status.

Prediction of radiosensitivity in primary central nervous system germ cell tumors using dynamic contrast-enhanced magnetic resonance imaging

Objective： To evaluate the feasibility of dynamic contrast-enhanced magnetic resonance imaging（DCEMRI） for predicting tumor response to radiotherapy in patients with suspected primary central nervous system（CNS） germ cell tumors（GCTs）.Methods： DCE-MRI parameters of 35 patients with suspected primary CNS GCTs were obtained prior to diagnostic radiation, using the Tofts and Kermode model. Radiosensitivity was determined in tumors diagnosed 2 weeks after radiation by observing changes in tumor size and markers as a response to MRI. Taking radiosensitivity as the gold standard, the cut-off value of DCE-MRI parameters was measured by receiver operating characteristic（ROC） curve. Diagnostic accuracy of DCE-MRI parameters for predicting radiosensitivity was evaluated by ROC curve.Results： A significant elevation in transfer constant（K^trans） and extravascular extracellular space（Ve）（P=0.000）, as well as a significant reduction in rate constant（Kep）（P=0.000） was observed in tumors. K^trans, relative K^trans, and relative Kep of the responsive group were significantly higher than non-responsive groups. No significant difference was found in Kep, Ve, and relative Ve between the two groups. Relative K^trans showed the best diagnostic value in predicting radiosensitivity with a sensitivity of 100%, specificity of 91.7%, positive predictive value（PPV） of 95.8%, and negative predictive value（NPV） of 100%.Conclusions： Relative K^trans appeared promising in predicting tumor response to radiation therapy（RT）. It is implied that DCE-MRI pre-treatment is a requisite step in diagnostic procedures and a novel and reliable approach to guide clinical choice of RT.

Dynamic contrast-enhanced magnetic resonance imaging of prostate cancer: A review of current methods and applications

In many areas of oncology, dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) has proven to be a clinically useful, non-invasive functional imaging technique to quantify tumor vasculature and tumor perfusion characteristics. Tumor angiogenesis is an essential process for tumor growth, proliferation, and metastasis. Malignant lesions demonstrate rapid extravasation of contrast from the intravascular space to the capillary bed due to leaky capillaries associated with tumor neovascularity. DCE-MRI has the potential to provide information regarding blood flow, areas of hypoperfusion, and variations in endothelial permeability and microvessel density to aid treatment selection, enable frequent monitoring during treatment and assess response to targeted therapy following treatment. This review will discuss the current status of DCE-MRI in cancer imaging, with a focus on its use in imaging prostate malignancies as well as weaknesses that limit its widespread clinical use. The latest techniques for quantification of DCE-MRI parameters will be reviewed and compared.

Photodissociation Dynamics of OCS at 217 nm

The S（1D2）＋CO（X1Σ＋） product channel from photodissociation of OCS at 217 nm has been measured using the DC slice velocity map imaging （VMI） technique in combination with resonance enhanced multiphoton ionization （REMPI）. Two diflerent REMPI intermediate states （1F3 and 1P1） and several pump-probe laser polarization geometries are used to detect the angular momentum polarization of the photofragmented S（1D2）. The molecular- frame polarization parameters, as well as the laboratory-frame anisotropy parameters, for individual rotational states of co-fragment CO, are determined using two diflerent full quantum theories. The measured total kinetic energy release spectrum from photodissociation of OCS indicates two dissociation channels, corresponding to the fast and slow recoiling velocities of S（1D2）, respectively. The slow channel is concluded to originate from an initial photoexcitation to the A（1A＇） state, followed by a non-adiabatic transition to the ground state. The fast channel is found to follow a coherent excitation to A（1A＇） and B（1A＇） states, where contributions of the two states are almost equal at 217 nm. The determined alignment and anisotropy parameters further indicate that the slow channel follows an incoherent excitation, while the fast channel follows a coherent excitation to A（1A＇） and B（1A＇） states with a phase di erence of π/2.

Comparison of shape representation methods for dynamic cell analysis

To evaluate the performance of basic shape representation methods for the description of dynamic cellular morphology, several frequently-used shape descriptors are compared. The methods are examined by using 50 lymphocyte video clips including two kinds of lymphocyte cells. Our goal is to represent cell shape in each frame accurately, meanwhile precisely classify the two groups of cells based on the cellular morphological variations in the video clips. Experimental results illustrate that in general the region-based shape descriptors outperform the contour-based ones, since the contourbased methods are excessively sensitive and ignorant to cellular internal information. Due to their robustness to noise, the region-based shape descriptors are suitable for dynamic cell representation. Although region-based methods are more time-consuming, they analyze the entire cell area.

Dynamic contrast-enhanced MRI versus ^(18)F-FDG PET/CT: Which is better in differentiation between malignant and benign solitary pulmonary nodules?

Objective： To prospectively compare the discriminative capacity of dynamic contrast enhanced-magnetic resonance imaging（DCE-MRI） with that of^18F-fluorodeoxyglucose（^18F-FDG） positron emission tomography/computed tomography（PET/CT） in the differentiation of malignant and benign solitary pulmonary nodules（SPNs）.Methods： Forty-nine patients with SPNs were included in this prospective study. Thirty-two of the patients had malignant SPNs, while the other 17 had benign SPNs. All these patients underwent DCE-MRI and ^18F-FDG PET/CT examinations. The quantitative MRI pharmacokinetic parameters, including the trans-endothelial transfer constant（K^trans）, redistribution rate constant（Kep）, and fractional volume（Ve）, were calculated using the Extended-Tofts Linear two-compartment model. The ^18F-FDG PET/CT parameter, maximum standardized uptake value（SUV（max））, was also measured. Spearman＇s correlations were calculated between the MRI pharmacokinetic parameters and the SUV（max） of each SPN. These parameters were statistically compared between the malignant and benign nodules. Receiver operating characteristic（ROC） analyses were used to compare the diagnostic capability between the DCE-MRI and ^18F-FDG PET/CT indexes.Results： Positive correlations were found between K^trans and SUV（max）, and between K（ep） and SUV（max）（P〈0.05）.There were significant differences between the malignant and benign nodules in terms of the K^trans, K（ep） and SUV（max） values（P〈0.05）. The areas under the ROC curve（AUC） of K^trans） K（ep） and SUV（max） between the malignant and benign nodules were 0.909, 0.838 and 0.759, respectively. The sensitivity and specificity in differentiating malignant from benign SPNs were 90.6% and 82.4% for K^trans; 87.5% and 76.5% for K（ep）; and 75.0% and 70.6%for SUV（max）, respectively. The sensitivity and specificity of K^trans and K（ep） were higher than those of SUV（max）, but there was no significant difference between them（P〉0.05）.Conclusions： DCE-MRI can be used to differentiate between benign and malignant SPNs and has the advantage of being radiation free.