Ideal Image Research Articles

A survey on training challenges in generative adversarial networks for biomedical image analysis

In biomedical image analysis, the applicability of deep learning methods is directly impacted by the quantity of image data available. This is due to deep learning models requiring large image datasets to provide high-level performance. Generative Adversarial Networks (GANs) have been widely utilized to address data limitations through the generation of synthetic biomedical images. GANs consist of two models. The generator, a model that learns how to produce synthetic images based on the feedback it receives. The discriminator, a model that classifies an image as synthetic or real and provides feedback to the generator. Throughout the training process, a GAN can experience several technical challenges that impede the generation of suitable synthetic imagery. First, the mode collapse problem whereby the generator either produces an identical image or produces a uniform image from distinct input features. Second, the non-convergence problem whereby the gradient descent optimizer fails to reach a Nash equilibrium. Thirdly, the vanishing gradient problem whereby unstable training behavior occurs due to the discriminator achieving optimal classification performance resulting in no meaningful feedback being provided to the generator. These problems result in the production of synthetic imagery that is blurry, unrealistic, and less diverse. To date, there has been no survey article outlining the impact of these technical challenges in the context of the biomedical imagery domain. This work presents a review and taxonomy based on solutions to the training problems of GANs in the biomedical imaging domain. This survey highlights important challenges and outlines future research directions about the training of GANs in the domain of biomedical imagery.

The Impact of Perfect Image Portrayal on TikTok (Douyin) on Appearance Anxiety Among Young Chinese Women

Social media, especially visual platforms such as Douyin, have greatly influenced the values of young Chinese people, especially young women. The prevalence of idealised body images and aesthetic standards on social media has contributed to physical anxiety and hurt self-cognition and mental health. The purpose of this study is to explore how the perfect image shaping on Douyin affects the appearance anxiety of young Chinese women, their mental health and self-perception. Analysing social media usage patterns highlights the significant trend of young women. Many respondents use social media for more than 30 minutes a day, especially on TikTok. These users often encounter idealised images. Despite widespread suspicion, more than half of them think that these images are real to some extent. This exposure leads to anxiety about appearance, and more than 25% of young women suffer from moderate anxiety. This anxiety has fuelled people’s desire for beauty or plastic surgery, and 62.5% of people try to achieve their ideal appearance through self-care and exercise. Popular beauty filters and image enhancement tools on social media further exacerbate this anxiety because they promote unrealistic beauty standards.

A Generative-Based Image Fusion Strategy for Visible-Infrared Person Re-Identification

Cross-modality person re-identification task is a challenging task aiming to recognize images of the same identity between different modalities. To alleviate the cross-modality discrepancies between images, existing approaches mainly guide models to mine modality invariant features. Although those approaches are effective, they lose the modality-specific features that include important information beneficial to VI-ReID. Therefore, some approaches are using generative adversarial networks to compensate for modality information. However, the quality of images generated by these methods is usually poor, and most of them focus only on the learning of modality-sharable features. To solve these problems, this paper proposes a generative-based cross-modality image fusion strategy (GC-IFS), which can generate high-quality cross-modality paired images and fuse the information of the two modalities. Firstly, considering the importance of the identity discriminative information of the generated image, we propose a contrastive-learning image generation (CLIG) network to generate cross-modality paired images. Meanwhile, to fully integrate and utilize the information of the two modalities and eliminate the influence of cross-modality discrepancies, we design a part-based dual multi-modality feature fusion (P-DMFF) module to extract the unified feature representation. Extensive experiments on SYSU-MM01 and RegDB datasets demonstrate that our strategy outperforms the state-of-the-art methods for the VI-ReID task.

Disrupting Anti-Spoofing Systems by Images of Consistent Identity

Disrupting Anti-Spoofing Systems by Images of Consistent Identity

IMAGE OF A HORSE AS A SYMBOL OF ETHNIC IDENTITY (on the example of Kazakh and Tuva theatres)

The article is devoted to the problem of cultural and ethnic identity in the national theatres of Kazakhstan and Tuva. In the national theatre the issue of socio-cultural ties is provided in theatrical performances through the manifestation on stage of cultural and national values, meanings and values as a reflection of ethnic identity, aesthetic and moral ideals of the people. Modern world theatre is a potential place of cultural forms reproduced by stage artists, offering to look through the eyes of the contemporary here and now, what we are today, what processes are taking place in the ethno-cultural society. The works of the authors of national theatres, as subjects of indigeneous culture, represent the presentation of cultural symbolic images, in which the ethnic identity of the people is reproduced. And in this connection, the question is raised how in modern conditions the ethnic is expressed in the national theatres of Kazakhstan and Tuva. The aim of the work is a comparative analysis of the symbolic image of the "horse" in the construction of the picture of the world in the national performances of the theatres of Kazakhstan and Tuva. The novelty of the study lies in the fact that the consideration of the concept of a "horse" as a symbolic image of cultural and ethnic identity in Kazakh and Tuvan culture in the context of a theatrical performance has not been the subject of cultural analysis. The theoretical and methodological basis of the article are the works of foreign, Kazakh (A.Sh. Mirzabekova, 2006), Russian (V.N. Badmaev, 2005,) and Tuvan scholars (Ch.K. Lamazhaa, 2018) who studied the problems of national identity, as well as the works of Kazakh and Tuvan theatre scholars, philologists, and cultural scientists. The source base is theatre productions: the Kazakh play "Kulager" (directed by Farhad Moldagaliev, Kazakhstan) and the Tuvan play "Egil, ezhim, egil!" (directed by Alexey Oorzhak, Tuva). (directed by Alexei Oorzhak, Tyva). On the basis of the cultural analysis of the image of the horse, the authors of the article substantiated the concept of "horse" as a symbol of freedom and independence in the theatrical art of Kazakhstan and Tuva", revealed the symbolic image of "horse" in the Kazakh performance, reflecting the ethnic identity and traditional culture of this people, conducted an analysis of the image of "horse" in the national drama of Tuvinians as a cultural element that ensures the preservation and transmission of traditional values of this people.

The Two new biomarkers: Bipolar Self, Bipolar EEG

Background: Although self theory was initially interested in narcissism, it began to explain depression over time. In our previous study, we showed that there was a relationship between self-inventory and mood disorder questionnaire scores in healthy individuals. Self-inventory defensive subscale scores of cases diagnosed with bipolar disorder were higher than healthy individuals. The aim of this study is to investigate whether there is a relationship between self-inventory scores and EEG spectral power densities in bipolar patients. Methods: For this purpose, 50 cases diagnosed with bipolar disorder according to DSM-V were evaluated consecutively during their regular check-ups in our outpatient clinic. Subjects who gave voluntary consent to participate in the study were required to be in remission period for at least 8 weeks. Self Inventory and EEG applied. Results: A relationship was found between compensatory grandiose self and FP1 alpha activity, and between defensive grandiose self and F3, Pz, T4, T5 beta activity (Table-1). There is a relationship between compensatory idealized parent image and FP1 delta ve theta, F7 theta, and between defensive idealized parent image and O1, O2 theta T6 beta activity. Conclusion: According to our results, self-pathology and bipolar disorder overlap electrophysiologically. This suggests that more investigation should be done on the structural origin of mood disorders, in other words, whether the predisposition is a trait or not.

Dual-purposing disulfiram for enhanced chemotherapy and afterglow imaging using chlorin e6 and semiconducting polymer combined strategy.

Rationale: One of the main challenges in chemotherapy is achieving high treatment efficacy while minimizing adverse events. Fully exploiting the therapeutic potential of an old drug and monitoring its effects in vivo is highly valuable, but often difficult to achieve. Methods: In this study, by encapsulating disulfiram (DSF) approved by US Food and Drug Administration, semiconducting polymer nanocomplex (MEHPPV), and Chlorin e6 into a polymeric matrix F127 via nanoprecipitation method, a nanosystem (FCMC) was developed for afterglow imaging guided cancer treatment. The characteristics, stability as well as the ability of singlet oxygen (1O2) production of FCMC were first carefully examined. Then, we studied the mechanism for enhanced anti-cancer efficiency and afterglow luminescence in vitro. For experiments in vivo, 4T1 subcutaneous xenograft tumor mice were injected with FCMC via the tail vein every three days and the antitumor effect of FCMC was evaluated by monitoring tumor volume and body weight every three day. Results: The nanosystem, which combines DSF with Ce6, can generates abundant 1O2 that enhances the antitumor activity of DSF. The in vivo results show that FCMC-treated group exhibits an obviously higher tumor-growth inhibition rate of 67.89% after 15 days of treatment, compared to the control group of F127@MEHPPV-CuET. Moreover, Ce6 also greatly enhances the afterglow luminescence intensity of MEHPPV and promotes the redshift of the afterglow emission towards the ideal near-infrared imaging window, thereby enabling efficient afterglow tumor imaging in vivo. Conclusions: This multifunctional nanoplatform not only improves the anticancer efficacy of DSF, but also enables monitoring tumor via robust afterglow imaging, thus exhibiting great potential for cancer therapy and early therapeutic outcome prediction.

MCE: Medical Cognition Embedded in 3D MRI feature extraction for advancing glioma staging.

In recent years, various data-driven algorithms have been applied to the classification and staging of brain glioma MRI detection. However, the restricted availability of brain glioma MRI data in purely data-driven deep learning algorithms has presented challenges in extracting high-quality features and capturing their complex patterns. Moreover, the analysis methods designed for 2D data necessitate the selection of ideal tumor image slices, which does not align with practical clinical scenarios. Our research proposes an novel brain glioma staging model, Medical Cognition Embedded (MCE) model for 3D data. This model embeds knowledge characteristics into data-driven approaches to enhance the quality of feature extraction. Approach includes the following key components: (1) Deep feature extraction, drawing upon the imaging technical characteristics of different MRI sequences, has led to the design of two methods at both the algorithmic and strategic levels to mimic the learning process of real image interpretation by medical professionals during film reading; (2) We conduct an extensive Radiomics feature extraction, capturing relevant features such as texture, morphology, and grayscale distribution; (3) By referencing key points in radiological diagnosis, Radiomics feature experimental results, and the imaging characteristics of various MRI sequences, we manually create diagnostic features (Diag-Features). The efficacy of proposed methodology is rigorously evaluated on the publicly available BraTS2018 and BraTS2020 datasets. Comparing it to most well-known purely data-driven models, our method achieved higher accuracy, recall, and precision, reaching 96.14%, 93.4%, 97.06%, and 97.57%, 92.80%, 95.96%, respectively.

The Influence of Maternity Wear Brand Image Innovation Elements on Consumer Behavior: A Grounded Theory Study

This grounded theory study investigates the influence of maternity wear brand image innovation elements on consumer behavior, addressing two main research questions: (1) How to innovate the brand image of maternity wear? and (2) What is the relationship between brand image innovation and consumer behavior in maternity wear? Maternity wear brands play a critical role in meeting the diverse needs of expectant mothers, yet in China, they often lack distinct brand identities and fail to cater to the varied preferences of pregnant women. Through a comprehensive research design, including literature review, grounded theory analysis, and empirical testing via questionnaire surveys, this study identifies six dimensions of brand image innovation in maternity wear: Product, Identity, Corporate, Marketing, Service, and Store image innovation, along with 21 specific indicators such as style and fabric innovation. The findings reveal a significant impact of each dimension of brand image innovation on consumer behavior. Theoretical and managerial implications highlight the study’s contribution in filling a research gap, providing a new framework for brand image research in maternity wear, and offering targeted recommendations for brand innovation efforts. This research expands understanding of the intricate relationship between consumer behavior and brand image, providing theoretical guidance for maternity wear companies to enhance brand appeal, meet diverse consumer needs, and ultimately improve sales and loyalty.

ОСОБЕННОСТИ ГОЛОСА СОПРАНО И ЕГО ИНТЕРПРЕТАЦИЯ: ТРАДИЦИЯ ПЕНИЯ И ВОЗМОЖНЫЕ ОБРАЗНЫЕ ВОПЛОЩЕНИЯ

The article is devoted to the description of the timbre of the soprano voice and its artistic semantics. It provides the definition of the term and a brief overview of the use of voice in operas by foreign composers. Technical fluency and mastery of the cantilena are put forward as essential properties of the voice. The article examines the coloristic features of the soprano voice, the repertoire for it, the connection of the voice with possible figurative interpretations and the emotional sphere. It is emphasised that the use of coloratura soprano is typical for European opera, while Russian composers prefer the properties of the lyrical timbre. It is noted that the vocal and aesthetic features of the coloratura soprano are suitable for the embodiment of fabulous images. The soprano is often the title character of the opera, the ideal image of a romantic heroine. The performer has to be fluent in singing technique and at the same time be able to creatively interpret a piece of music according to its style. The verbal text in opera is important, as it affects the formation of the musical fabric and can serve as an additional means of expression. In Russian musical art, soprano characters represent beautiful heroines of historical, epic, lyrical, comic, dramatic, psychological works.

Шествие: иконография и литургическое действо в эпоху Ивана Грозного

The article deals with Novgorod and Moscow liturgical rites with regard to the Procession on Palm Sunday. They are compared with the Byzantine rites in order to establish the causes and time of the appearance of the tsar in the Moscow divine service. It was believed that Metropolitan Macarius had brought the rite of the Novgorod Saint Sophia Cathedral to Moscow while the form of the Novgorod rite was shaped under the influence of Donatio Constantini as represented in the Novgorod literature (The tale of the white klobuk). The study has revealed no influence of Donatio Constantini on the Novgorod rite. Moscow processions, or litia were established in 1551 by the Decree of the Hundred-Chapter Synod. The significance of the processions as a form of liturgy has an iconographical confirmation (the icon ‘Blessed Be the Host of the Heavenly Tsar’”). The ideological content of the litia as a prayer request formulated in the Decree corresponds to liturgical texts (Coronation rite), epistles and painted programs (painting of the Golden Chamber of the Moscow Kremlin) of Metropolitan Macarius. They are aimed at forming an ideal image of the Orthodox tsar, whose main feature is piety – the guarantee of the welfare of his state. The participation of Ivan the Terrible in the Procession on Palm Sunday, in our opinion, can be attributed to the liturgical acts of Metropolitan Macarius.

An injectable fluorescent and iodinated hydrogel for preoperative localization and dual image-guided surgery of pulmonary nodules.

The widespread use of video-assisted thoracoscopic surgery (VATS) has triggered the rapid expansion in the field of computed tomography (CT)-guided preoperative localization and near-infrared (NIR) fluorescence image-guided surgery. However, its broader application has been hindered by the absence of ideal imaging contrasts that are biocompatible, minimally invasive, highly resolvable, and perfectly localized within the diseased tissue. To achieve this goal, we synthesize a dextran-based fluorescent and iodinated hydrogel, which can be injected into the tissue and imaged with both CT and NIR fluorescence modalities. By finely tuning the physical parameters such as gelation time and composition of iodinated oil (X-ray contrast agent) and indocyanine green (ICG, NIR fluorescence dye), we optimize the hydrogel for prolonged localization at the injected site without losing the dual-imaging capability. We validate the effectiveness of the developed injectable dual-imaging platform by performing image-guided resection of pulmonary nodules on tumor-bearing rabbits, which are preoperatively localized with the hydrogel. The injectable dual-imaging marker, therefore, can emerge as a powerful tool for surgical guidance.

Семантическая структура образа Я старшеклассников – пользователей социальных сетей

The article presents the results of the study of the semantic assessment by senior pupils, who are active users of social networks, of their real, virtual, and ideal self. The author verified the hypothesis, which suggests actualizing the characteristics of an ideal image in social networks. The sampling included 180 people who rated stimulus images according to 43 scales of a specialized semantic differential. The study has revealed that categorical criteria of self-image assessment are arousal, sociability, successfulness, joyfulness, gracefulness (beauty), anxiety, and honesty. It has been found, that the senior pupils’ view of both their real and virtual self is far from the semantics of the ideal image on most of the criteria. The network image is delegated with vulnerable characteristics of the real self, but low level of anxiety brings pupils’ virtual and ideal self closer.

Investigation into Online English Learners’ L2 Motivation Using Imagery and Online Counselling Sessions

In this study, a motivational program using imagery and online counselling sessions was designed based on the theory of the L2 Motivational Self System. This study aimed to investigate the effectiveness of the program by conducting a mixed-method approach, 50 participants took part in 7 imagery training sessions and a pre-post survey. Additionally, among these participants, 20 also engaged in 2 online counseling sessions and focus group interviews. The motivational program using imagery and online counseling sessions was seen to have a significant positive effect on students' L2 Motivational Self System. In particular, as a result of comparing the average values of the pre-post questionnaire, the biggest changes were shown in the categorizes of Ideal Self, Imagery and Visualization, and Attitudes toward Learning English. By utilizing imagery training and online counselling sessions along with English learning, not only were the students' capability of visualizing the image of themselves enhanced, but also positive attitudes towards English education were induced. This led to the fostering of students' motivation in learning English and to the improvement of their L2 Ideal Self Image. Of significant note are the findings in the qualitative data analysis, which show that emotional difficulties in students' English learning, such as academic stress and anxiety, can be alleviated through online counseling sessions, thereby helping them to sustain their learning motivation, Implications of the study are presented and discussed.

새록 대안학교 교육과정에 대한 졸업생 경험 이해

Objectives This study tries to understand and interpret graduates' experience about Saerok Alternative school curriculum.
 Methods It is a case study of the Saerok school curriculum. Among the graduates who graduated for more than 20 years, a total of 21 people were interviewed. From data collection to coding, description, analysis, and interpretation were all carried out in a narrative manner.
 Results Compared to the school's development, the curriculum was constructed of general and alternative subjects with different contents and formats, after-school activities centered on clubs, various autonomous activities, and dormitory life. Each identity and school image formed in the process had an important influence on career choice. Many of the participants went to college and some participated in society, but they had to experience a career plus curriculum in which they tried on their own, suffering from a gap from reality.
 Conclusions The Saerok Alternative school curriculum can be understood as a text for life led by students and compared to general schools, it can be understood as a null curriculum. The graduate's career path was based on their experiences at school. On the other hand, there were many trials and errors in the process of finding a career path because it was far from the stereotyped norms and values of society.

ANALYSIS OF DILALAH TASHAWWURIYYAH (CONCEPTUAL METHAPOR) IN THE AL-QUR'AN SURAH YASIN / ANALISIS DILALAH TASHAWWURIYYAH (METAFORA KONSEPTUAL) DALAM AL-QUR'AN SURAH YASIN

This research aims to discover and explain the types of dilalah tashawwuriyyah (conceptual metaphor) and the image schemes contained in the Al-Qur'an Surah Yasin. The general theory used in this study is the conceptual theory of cognitive semantics from Lakoff & Johnson, while the theory used to determine the type of metaphor is conceptual meaning theory and the theory used to determine the image schema is Cruse & Croft's theory. The method used in this research is a descriptive qualitative method. To analyze the conceptual theory of Arabic using the matching method with Arabic dictionary and Tafsir as tools to explore further the meaning contained in the theory to find conceptual meaning, because in understanding the Qur'an is not enough to use only one point of view. The results of this research show that there are 5 dilalah tashawuriyyah (conceptual metaphors) found in Surah Yasin, namely 3 types of systematic metaphors and 2 types of anthropomorphic metaphors. The metaphor has 3 image schemas, namely identity (matching), existence (process), and force (compulsion) image schemas.

Contested Self-image Because of Excessive Use of Social Media: A Qualitative Study of Female Instagram Users of Fast University Islamabad

Adolescent girls and young women may be influenced by social media settings to participate in social comparison, leading to feelings of inadequacy and body dissatisfaction. Instagram usage was nevertheless frequently observed to have notable special effects on body dissatisfaction, eating disorders, and inappropriate dieting behaviours in an attempt to achieve an ideal body image. From this research, it was shown that most young girls think that in Pakistani culture, certain body types are marketed on Instagram and by Instagram influencers. Social media has grown in popularity, particularly among university students and adolescent girls. Instagram may be a harmful mirror in which young women see their bodies in a distorted way. To look better, respondents also said that they use Instagram to keep up with the latest fashion and cosmetics trends.

Identification of the Original Images

In social networks, people usually communicate online by posting and passing images, people will find that there are many similar or even visually identical images. When the images determine whether the published information is true or false, original images became crucial, and at the same time, deep learning excelled in image identification. Combining the original image identification and deep learning methods, this paper proposes the original image identification method based on the deep network models, aiming to use the deep network models to identify the original images between the original images and a bunch of variant images of the original images, and obtain satisfactory results. In this way, through the trained network models, the original images can be identified and can help the viewers to determine the correctness of the information. Experimental results verify the feasibility, effectiveness and security of the proposed method.

The Pediatric Neuroradiologist's Practical Guide to Capture and Evaluate Pre- and Postoperative Velopharyngeal Insufficiency.

Up to 30% of children with cleft palate will develop a severe speech disorder known as velopharyngeal insufficiency. Management of velopharyngeal insufficiency typically involves structural and functional assessment of the velum and pharynx by endoscopy and/or videofluoroscopy. These methods cannot provide direct evaluation of underlying velopharyngeal musculature. MR imaging offers an ideal imaging method, providing noninvasive, high-contrast, high-resolution imaging of soft-tissue anatomy. Furthermore, focused-speech MR imaging techniques can evaluate the function of the velum and pharynx during sustained speech production, providing critical physiologic information that supplements anatomic findings. The use of MR imaging for velopharyngeal evaluation is relatively novel, with limited literature describing its use in clinical radiology. Here we provide a practical approach to perform and interpret velopharyngeal MR imaging examinations. This article discusses the velopharyngeal MR imaging protocol, methods for interpreting velopharyngeal anatomy, and examples illustrating its clinical applications. This knowledge will provide radiologists with a new, noninvasive tool to offer to referring specialists.

A diagnostic report supervised deep learning model training strategy for diagnosis of COVID-19

COVID-19 is a highly contagious infectious disease that necessitates timely assessment and effective diagnosis, although it is no longer a health emergency. Most existing computer-aided diagnosis systems for COVID-19 can achieve high accuracy, but they show insufficient generalization performance and weak interpretability. To address these issues, we propose diagnostic report supervised contrastive learning (DRSCL), a model training strategy that incorporates textual information from medical reports into model pretraining and then only transfers the pretrained image encoder into model inference. Due to the issue of data recurrence in medical diagnosis reports, which is common in the medical domain and can cause nonconvergence of the pretraining stage of DRSCL, we improve the loss function calculation of contrastive learning by integrating an operation to merge identical text or image features. In addition, for the fine-tuning and inference stage of DRSCL, we design a hierarchical fine-tuning strategy to better evaluate the pretraining performance and importance of each module. In case study, we build a medical image-text pair dataset of lung diseases for pretraining, with samples collected from hospitals in East China, and then conduct the fine-tuning and inference operation of DRSCL with a publicly available SARS-CoV-2 dataset. The comparative experimental results show that DRSCL helps all involved image encoders obtain better classification accuracy and superior generalization performance in the given COVID-19-related diagnostic application. This finding indicates that DRSCL enhances deep models to learn more deep information with supervision of medical textual information. Furthermore, we adopt the Grad-CAM method to visualize pretrained models, and the results demonstrate that the DRSCL strategy is advantageous for improving model interpretability.