Journal of Imaging最新文献

{"title":"Distributed Sparse Manifold-Constrained Optimization Algorithm in Linear Discriminant Analysis.","authors":"Yuhao Zhang, Xiaoxiang Chen, Manlong Feng, Jingjing Liu","doi":"10.3390/jimaging11030081","DOIUrl":"10.3390/jimaging11030081","url":null,"abstract":"<p><p>In the field of video image processing, high definition is one of the main directions for future development. Faced with the curse of dimensionality caused by the increasingly large amount of ultra-high-definition video data, effective dimensionality reduction techniques have become increasingly important. Linear discriminant analysis (LDA) is a supervised learning dimensionality reduction technique that has been widely used in data preprocessing for dimensionality reduction and video image processing tasks. However, traditional LDA methods are not suitable for the dimensionality reduction and processing of small high-dimensional samples. In order to improve the accuracy and robustness of linear discriminant analysis, this paper proposes a new distributed sparse manifold constraint (DSC) optimization LDA method, called DSCLDA, which introduces L2,0-norm regularization for local sparse feature representation and manifold regularization for global feature constraints. By iterating the hard threshold operator and transforming the original problem into an approximate non-convex sparse optimization problem, the manifold proximal gradient (ManPG) method is used as a distributed iterative solution. Each step of the algorithm has an explicit solution. Simulation experiments have verified the correctness and effectiveness of this method. Compared with several advanced sparse linear discriminant analysis methods, this method effectively improves the average classification accuracy by at least 0.90%.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the First Metacarpal Bone Head and Distal Radius Bone Architecture Using Fractal Analysis of Adolescent Hand-Wrist Radiographs.","authors":"Kader Azlağ Pekince, Adem Pekince","doi":"10.3390/jimaging11030082","DOIUrl":"10.3390/jimaging11030082","url":null,"abstract":"<p><p>The purpose of this study was to investigate changes in bone trabecular structure during adolescence using the fractal analysis (FA) method on hand-wrist radiographs (HWRs) and to evaluate the relationship of these changes with pubertal growth stages. HWRs of healthy individuals aged 8-18 years were included (<i>N</i> = 600). Pubertal stages were determined by the Fishman method and divided into 10 groups (early puberty [EP], pre-peak [PRPK], peak [PK], post-peak [PTPK], late puberty [LP]). FA was performed using FIJI (ImageJ) software and the BoneJ plugin on circular regions of interest (ROIs) selected from the first metacarpal bone head and distal radius. Image processing steps were applied according to the White and Rudolph method. Differences between groups were statistically evaluated. Fractal dimension (FD) values of the distal radius (RAFAM) and metacarpal bone head (MAFAM) showed significant differences according to pubertal growth stages (<i>p</i> < 0.05). The highest FD value was observed in the LP group, and the lowest FD value was observed in the EP group (except MAFAM in females). FD generally increased from EP to LP in the whole population, but a significant decrease was observed in all groups during the PK period. This decrease was more pronounced in RAFAM of males. These findings suggest a potential decrease of bone mechanical properties in the PK, which is found the be more suitable for orthodontic treatment in the literature. FA on HWRs is a useful and sensitive tool for quantitatively assessing pubertal changes in trabecular bone microarchitecture. The findings demonstrate a significant decrease in FD in both bone regions during the pubertal growth spurt, particularly at the peak period. This may indicate a temporary reduction in bone mechanical strength during this critical stage and could contribute to increased distal radius fracture incidence. Clinically, the relationship between FD and pubertal stages suggests this method could serve as a valuable biomarker in orthodontic treatment planning, allowing for optimized timing of interventions. Furthermore, it may aid in pediatric fracture risk assessment, potentially leading to preventative strategies for high-risk individuals.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11942856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing Diagnostic Reference Levels for Mammography Digital Breast Tomosynthesis, Contrast Enhance, Implants, Spot Compression, Magnification and Stereotactic Biopsy in Dubai Health Sector.","authors":"Entesar Z Dalah, Maryam K Alkaabi, Nisha A Antony, Hashim M Al-Awadhi","doi":"10.3390/jimaging11030079","DOIUrl":"10.3390/jimaging11030079","url":null,"abstract":"<p><p>The aim of this patient dose review is to establish a thorough diagnostic reference level (DRL) system. This entails calculating a DRL value for each possible image technique/view considered to perform a diagnostic mammogram in our practice. Diagnostic mammographies from a total of 1191 patients who underwent a diagnostic mammogram study in our designated diagnostic mammography center were collected and retrospectively analyzed. The DRL representing our health sector was set as the median of the mean glandular dose (MGD) for each possible image technique/view, including the 2D standard bilateral craniocaudal (LCC/RCC) and mediolateral oblique (LMLO/RMLO), the 2D bilateral spot compression CC and MLO (RSCC/LSCC and RSMLO/LSMLO), the 2D bilateral spot compression with magnification (RMSCC/LMSCC and RMSMLO/LMSMLO), the 3D digital breast tomosynthesis CC and MLO (RCC/LCC and RMLO/LMLO), the 2D bilateral implant CC and MLO (RIMCC/LIMCC and RIMMLO/LIMMLO), the 2D bilateral contrast enhanced CC and MLO (RCECC/LCECC and RCEMLO/LCEMLO) and the 2D bilateral stereotactic biopsy guided CC (SBRCC/SBLCC). This patient dose review revealed that the highest MGD was associated with the 2D bilateral spot compression with magnification (MSCC/MSMLO) image view. For the compressed breast thickness (CBT) group 60-69 mm, the median and 75th percentile of the MGD values obtained were MSCC: 3.35 and 3.96, MSMLO: 4.14 and 5.25 mGy respectively. Obvious MGD variations were witnessed across the different possible views even for the same CBT group. Our results are in line with the published DRLs when using same statistical quantity and CBT group.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Method to Compute the Contact Surface Area Between an Organ and Cancer Tissue.","authors":"Alessandra Bulanti, Alessandro Carfì, Paolo Traverso, Carlo Terrone, Fulvio Mastrogiovanni","doi":"10.3390/jimaging11030078","DOIUrl":"10.3390/jimaging11030078","url":null,"abstract":"<p><p>The contact surface area (CSA) quantifies the interface between a tumor and an organ and is a key predictor of perioperative outcomes in kidney cancer. However, existing CSA computation methods rely on shape assumptions and manual annotation. We propose a novel approach using 3D reconstructions from computed tomography (CT) scans to provide an accurate CSA estimate. Our method includes a segmentation protocol and an algorithm that processes reconstructed meshes. We also provide an open-source implementation with a graphical user interface. Tested on synthetic data, the algorithm showed minimal error and was evaluated on data from 82 patients. We computed the CSA using both our approach and Hsieh's method, which relies on subjective CT scan measurements, in a double-blind study with two radiologists of different experience levels. We assessed the correlation between our approach and the expert radiologist's measurements, as well as the deviation of both our method and the less experienced radiologist from the expert's values. While the mean and variance of the differences between the less experienced radiologist and the expert were lower, our method exhibited a slight deviation from the expert's, demonstrating its reliability and consistency. These findings are further supported by the results obtained from synthetic data testing.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11942950/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Chips on the Threaded Part of Cosmetic Glass Bottles.","authors":"Daiki Tomita, Yue Bao","doi":"10.3390/jimaging11030077","DOIUrl":"10.3390/jimaging11030077","url":null,"abstract":"<p><p>Recycled glass has been the focus of attention owing to its role in reducing plastic waste and further increasing the demand for glass containers. Cosmetics glass bottles require strict quality inspections because of the frequent handling, safety concerns, and other factors. During manufacturing, glass bottles sometimes develop chips on the top surface, rim, or screw threads of the bottle mouth. Conventionally, these chips are visually inspected by inspectors; however, this process is time consuming and prone to inaccuracies. To address these issues, automatic inspection using image processing has been explored. Existing methods, such as dynamic luminance value correction and ring-shaped inspection gates, have limitations: the former relies on visible light, which is strongly affected by natural light, and the latter acquires images directly from above, resulting in low accuracy in detecting chips on the lower part of screw threads. To overcome these challenges, this study proposes a method that combines infrared backlighting and image processing to determine the range of screw threads and detect chips accurately. Experiments were conducted in an experimental environment replicating an actual factory production line. The results confirmed that the detection accuracy of chipping was 99.6% for both good and defective bottles. This approach reduces equipment complexity compared to conventional methods while maintaining high inspection accuracy, contributing to the productivity and quality control of glass bottle manufacturing.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943122/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduction of Uneven Brightness and Ghosts of Aerial Images Using a Prism in a Micromirror Array Plate.","authors":"Kaito Shoji, Yuto Osada, Atsutoshi Kurihara, Yue Bao","doi":"10.3390/jimaging11030075","DOIUrl":"10.3390/jimaging11030075","url":null,"abstract":"<p><p>A micro-mirror array plate is a type of aerial image display that allows an observer to touch the aerial image directly. The problem with this optical element is that it produces stray light, called a ghost, which reduces the visibility of the aerial image. Conventional methods can suppress the occurrence of ghosts; however, depending on the observation position, uneven luminance is produced in aerial images. Therefore, in this study, we proposed a method for eliminating ghosts while suppressing the unevenness in the luminance of an aerial image using a prism. In the proposed device, a prism is placed between the liquid crystal display and the diffuser, which is the light source of the aerial display. The experimental results showed that the proposed method can suppress the unevenness in the luminance of aerial images better than the conventional ghost removal methods and can reduce the formation of ghosts better than the micromirror array plate alone. Therefore, the proposed method can be shown to be a ghost removal method that can suppress unevenness in the brightness of aerial images.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11942687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GM-CBAM-ResNet: A Lightweight Deep Learning Network for Diagnosis of COVID-19.","authors":"Junjiang Zhu, Yihui Zhang, Cheng Ma, Jiaming Wu, Xuchen Wang, Dongdong Kong","doi":"10.3390/jimaging11030076","DOIUrl":"10.3390/jimaging11030076","url":null,"abstract":"<p><p>COVID-19 can cause acute infectious diseases of the respiratory system, and may probably lead to heart damage, which will seriously threaten human health. Electrocardiograms (ECGs) have the advantages of being low cost, non-invasive, and radiation free, and is widely used for evaluating heart health status. In this work, a lightweight deep learning network named GM-CBAM-ResNet is proposed for diagnosing COVID-19 based on ECG images. GM-CBAM-ResNet is constructed by replacing the convolution module with the Ghost module (GM) and adding the convolutional block attention module (CBAM) in the residual module of ResNet. To reveal the superiority of GM-CBAM-ResNet, the other three methods (ResNet, GM-ResNet, and CBAM-ResNet) are also analyzed from the following aspects: model performance, complexity, and interpretability. The model performance is evaluated by using the open 'ECG Images dataset of Cardiac and COVID-19 Patients'. The complexity is reflected by comparing the number of model parameters. The interpretability is analyzed by utilizing Gradient-weighted Class Activation Mapping (Grad-CAM). Parameter statistics indicate that, on the basis of ResNet19, the number of model parameters of GM-CBAM-ResNet19 is reduced by 45.4%. Experimental results show that, under less model complexity, GM-CBAM-ResNet19 improves the diagnostic accuracy by approximately 5% in comparison with ResNet19. Additionally, the interpretability analysis shows that CBAM can suppress the interference of grid backgrounds and ensure higher diagnostic accuracy under lower model complexity. This work provides a lightweight solution for the rapid and accurate diagnosing of COVD-19 based on ECG images, which holds significant practical deployment value.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11942712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deepfake Media Forensics: Status and Future Challenges.","authors":"Irene Amerini, Mauro Barni, Sebastiano Battiato, Paolo Bestagini, Giulia Boato, Vittoria Bruni, Roberto Caldelli, Francesco De Natale, Rocco De Nicola, Luca Guarnera, Sara Mandelli, Taiba Majid, Gian Luca Marcialis, Marco Micheletto, Andrea Montibeller, Giulia Orrù, Alessandro Ortis, Pericle Perazzo, Giovanni Puglisi, Nischay Purnekar, Davide Salvi, Stefano Tubaro, Massimo Villari, Domenico Vitulano","doi":"10.3390/jimaging11030073","DOIUrl":"10.3390/jimaging11030073","url":null,"abstract":"<p><p>The rise of AI-generated synthetic media, or deepfakes, has introduced unprecedented opportunities and challenges across various fields, including entertainment, cybersecurity, and digital communication. Using advanced frameworks such as Generative Adversarial Networks (GANs) and Diffusion Models (DMs), deepfakes are capable of producing highly realistic yet fabricated content, while these advancements enable creative and innovative applications, they also pose severe ethical, social, and security risks due to their potential misuse. The proliferation of deepfakes has triggered phenomena like \"Impostor Bias\", a growing skepticism toward the authenticity of multimedia content, further complicating trust in digital interactions. This paper is mainly based on the description of a research project called FF4ALL (FF4ALL-Detection of Deep Fake Media and Life-Long Media Authentication) for the detection and authentication of deepfakes, focusing on areas such as forensic attribution, passive and active authentication, and detection in real-world scenarios. By exploring both the strengths and limitations of current methodologies, we highlight critical research gaps and propose directions for future advancements to ensure media integrity and trustworthiness in an era increasingly dominated by synthetic media.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Typical Diagnostic Reference Levels of Radiation Exposure on Neonates Under 1 kg in Mobile Chest Imaging in Incubators.","authors":"Ioannis Antonakos, Matina Patsioti, Maria-Eleni Zachou, George Christopoulos, Efstathios P Efstathopoulos","doi":"10.3390/jimaging11030074","DOIUrl":"10.3390/jimaging11030074","url":null,"abstract":"<p><p>The purpose of this study is to determine the typical diagnostic reference levels (DRLs) of radiation exposure values for chest radiographs in neonates (<1 kg) in mobile imaging at a University Hospital in Greece and compare these values with the existing DRL values from the literature. Patient and dosimetry data, including age, sex, weight, tube voltage (kV), tube current (mA), exposure time (s), exposure index of a digital detector (S), and dose area product (DAP) were obtained from a total of 80 chest radiography examinations performed on neonates (<1 kg and <30 days old). All examinations were performed in a single X-ray system, and all data (demographic and dosimetry data) were collected from the PACS of the hospital. Typical radiation exposure values were determined as the median value of DAP and ESD distribution. Afterward, these typical values were compared with DRL values from other countries. Three radiologists reviewed the images to evaluate image quality for dose optimization in neonatal chest radiography. From all examinations, the mean value and standard deviation of DAP was 0.13 ± 0.11 dGy·cm² (range: 0.01-0.46 dGy·cm²), and ESD was measured at 11.55 ± 4.96 μGy (range: 4.01-30.4 μGy). The typical values in terms of DAP and ESD were estimated to be 0.08 dGy·cm² and 9.87 μGy, respectively. The results show that the DAP value decreases as the exposure index increases. This study's typical values were lower than the DRLs reported in the literature because our population had lower weight and age. From the subjective evaluation of image quality, it was revealed that the vast majority of radiographs (over 80%) met the criteria for being diagnostic as they received an excellent rating in terms of noise levels, contrast, and sharpness. This study contributes to the recording of typical dose values in a sensitive and rare category of patients (neonates weighing <1 kg) as well as information on the image quality of chest X-rays that were performed in this group.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concealed Weapon Detection Using Thermal Cameras.","authors":"Juan D Muñoz, Jesus Ruiz-Santaquiteria, Oscar Deniz, Gloria Bueno","doi":"10.3390/jimaging11030072","DOIUrl":"10.3390/jimaging11030072","url":null,"abstract":"<p><p>In an era where security concerns are ever-increasing, the need for advanced technology to detect visible and concealed weapons has become critical. This paper introduces a novel two-stage method for concealed handgun detection, leveraging thermal imaging and deep learning, offering a potential real-world solution for law enforcement and surveillance applications. The approach first detects potential firearms at the frame level and subsequently verifies their association with a detected person, significantly reducing false positives and false negatives. Alarms are triggered only under specific conditions to ensure accurate and reliable detection, with precautionary alerts raised if no person is detected but a firearm is identified. Key contributions include a lightweight algorithm optimized for low-end embedded devices, making it suitable for wearable and mobile applications, and the creation of a tailored thermal dataset for controlled concealment scenarios. The system is implemented on a chest-worn Android smartphone with a miniature thermal camera, enabling hands-free operation. Experimental results validate the method's effectiveness, achieving an mAP@50-95 of 64.52% on our dataset, improving state-of-the-art methods. By reducing false negatives and improving reliability, this study offers a scalable, practical solution for security applications.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11942835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}