[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-460745-105":59,"doc-detail-460745-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","lightweight-dual-watermarking-framework-for-medical-image-authentication-and-integrity-preservation","Lightweight dual-watermarking framework for medical image authentication and integrity preservation","","Medical image authentication is essential for secure healthcare, where verifying that diagnostic images remain unaltered and truly originate from trusted sources directly supports safe clinical decisions. This work proposes a lightweight dual watermarking framework that embeds a machine-readable QR code and a hospital logo into medical images via a hybrid DWT-DCT frequency-domain method. A compact CNN decoder extracts the watermarks using an enhanced loss combining MSE, SSIM, and Sobel edge loss to maintain imperceptibility, low computation cost, and robustness against noise and geometric attacks while preserving image quality and structural integrity.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/lightweight-dual-watermarking-framework-for-medical-image-authentication-and-integrity-preservation/460745/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/lightweight-dual-watermarking-framework-for-medical-image-authentication-and-integrity-preservation/460745.png","ImageObject",300,407,{"name":92,"@type":93},"Genevieve","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the proposed dual-watermarking framework embed into medical images?","Question",{"text":112,"@type":113},"It embeds a machine-readable QR code and a hospital logo into medical images, enabling verification of authentication and integrity.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How are watermarks embedded and extracted in the proposed method?",{"text":117,"@type":113},"The encoder uses a hybrid frequency-domain approach combining Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT), while a lightweight CNN decoder is trained to extract the watermarks efficiently.",{"name":119,"@type":110,"acceptedAnswer":120},"What attacks does the framework test for robustness?",{"text":121,"@type":113},"The model is evaluated under Salt & Pepper noise, median filtering, rotation, and cropping to confirm watermark resilience under common signal and geometric manipulations.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},460745,1791427507,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1374391974585,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nLightweight dual-watermarking framework for medical image authentication and integrity preservation  \nRizwanTaj1􀀍, Saima Kanwal2, Amjad Alsirhani3, FaeizAlserhani4, RayanAlanazi3 & Arslan Ali5  \nMedical image authentication plays a vital role in secure healthcare industries, where assuring the integrity and authenticity of diagnostic images is critical for safe clinical decisions. This study presentsa robust, dual watermarking framework that embeds a machine-readable QR code and a hospital logo into medical images using a hybrid frequency-domain method combining Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) . A lightweight Convolutional Neural Network (CNN) decoder is developed for efficient watermark extraction, optimized through a novel enhanced loss function that integrates Mean Squared Error (MSE), Structural Similarity Index (SSIM), and Sobel edge loss. The encoder-decoder framework ensures imperceptibility, low computational cost, and resilience to standard signal and geometric attacks. The model is tested against Salt & Pepper noise, median filtering, rotation, and cropping to validate robustness. The proposed scheme achieves high watermark extraction fidelity with a Peak Signal-to-Noise Ratio (PSNR) ranging from 64.87 to 68.75 dBand Normalized Correlation (NC) values consistently reaching 1.0 under several attacks, demonstrating an average improvement of 28–35% in PSNR and 12–15% in NC. Furthermore, the lightweight CNN demonstrates a small model size of 0.65 MB with real-time inference capability, making it suitable for embedded and resource-constrained medical devices. The results confirm that the proposed dual watermarking method maintains visual quality, structural integrity, and security of medical images while ensuring efficient and accurate watermark retrieval.  \nKeywords CNN, DWT-DCT, Digital watermarking, Medical imaging  \nThe process of digitalization has revolutionized healthcare by increasing the use of medical imaging technology and spreading the use of electronic health records. Medical imaging, which now includes the modalities of X-rays, MRIs, CT scans, and ultrasound images, has become an indispensable part of modern diagnostics, a key that helps make correct clinical judgments and evidence-based decisions. However, the increased use of internet and cloud servers to store and distribute such sensitive data can be a source of new threats to their security, such as unauthorized access, data alteration, and loss of intellectual property. As a result, data integrity, authenticity, and privacy protection are central concerns of healthcare institutions across the globe1,2. Several techniques have been developed to ensure the security of medical data, including cryptography, steganography, and digital watermarking. Cryptography primarily protects the data during transmission through encryption, while steganography conceals the information within other media to prevent unauthorized detection. However, both techniques may fail to ensure direct content-level integrity of medical images once they are decoded or accessed. Digital watermarking, on the other hand, embeds authentication or ownership information directly into the medical image itself, allowing verification of integrity, origin, and tamper detection without requiring the original image. Therefore, this study adopts a watermarking-based approach to achieve both authentication and integrity preservation within the medical imaging workflow.  \n1School of Computer Science, University of Wah, Quaid Avenue, Wah Cantt, Pakistan. 2School of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu, China. 3Department of Computer Sciences, College of Computer and Information Sciences, Jouf University, Sakaka 72388, Al Jouf, Saudi Arabia. 4Department of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf Univer","cbCaiv5kMkVbW38z","https://ap.wps.com/l/cbCaiv5kMkVbW38z","pdf",3357350,18,"English","# Introduction\n## Security needs in medical imaging\n## Limits of cryptography and steganography\n## Role of digital watermarking\n# Related Concepts\n## Traditional watermarking domains\n## Limitations under modern attacks\n## Deep learning and CNN-based watermarking","[{\"question\":\"What does the proposed dual-watermarking framework embed into medical images?\",\"answer\":\"It embeds a machine-readable QR code and a hospital logo into medical images, enabling verification of authentication and integrity.\"},{\"question\":\"How are watermarks embedded and extracted in the proposed method?\",\"answer\":\"The encoder uses a hybrid frequency-domain approach combining Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT), while a lightweight CNN decoder is trained to extract the watermarks efficiently.\"},{\"question\":\"What attacks does the framework test for robustness?\",\"answer\":\"The model is evaluated under Salt \\u0026 Pepper noise, median filtering, rotation, and cropping to confirm watermark resilience under common signal and geometric manipulations.\"}]","Lightweight dual-watermarking framework for medical image authentication and integrity preservation | PDF",1790759391,45]