DermCompressNet: integrated CD-ConvNet and discrete cosine transform for dermoscopic images compression DOI Creative Commons

Radwa A. Elsawy,

Mohammed Abo‐Zahhad, Maram A. Wahba

et al.

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 21, 2024

Abstract Telemedicine has a critical role in healthcare by supporting the information exchange between patients and physicians as well for consultation. Such technology urgent requirements storage reduction efficient use of transmission channel bandwidth. can be achieved efficiently via developing accurate medical image compression techniques. For diagnosis, lossless methods are recommended. However, tradeoff ratio (CR) preservation quality is still challenging. On other hand, advantages convolutional neural networks inspired this work to design novel proposed system dermoscopic based on integration direction-ConvNet (CD-ConvNet) decompression (DD-ConvNet) with discrete cosine transform (DCT) Huffman coding, called DermCompressNet. To reconstruct high-quality at receiver, inverse processes using DD-ConvNet network were followed. The was evaluated measuring several metrics, namely mean square error (MSE), peak signal-to-noise (PSNR), structural similarity index measure (SSIM), along CR, computational time (CT). experimental results 34.6 dB, 2.5, 0.85, 56% PSNR, MSE, SSIM, respectively. A comparison studies JPEG state-of-the-art proved superiority system, showing23%, 16%, 4.3%, 1.8% improvements respectively, compared JPEG.

Language: Английский

Deep learning approaches to detect breast cancer: a comprehensive review DOI

Amir Mohammad Sharafaddini,

Kiana Kouhpah Esfahani,

N. Mansouri

et al.

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 20, 2024

Language: Английский

Citations

12

Digital image watermarking using deep learning: A survey DOI
Khalid M. Hosny, Amal Magdi,

Osama M. Elkomy

et al.

Computer Science Review, Journal Year: 2024, Volume and Issue: 53, P. 100662 - 100662

Published: Aug. 1, 2024

Language: Английский

Citations

11

Artificial Intelligence and Algorithmic Approaches of Health Security Systems: A Review DOI Creative Commons

Savina Mariettou,

Constantinos Koutsojannis,

Vassilios Triantafillou

et al.

Algorithms, Journal Year: 2025, Volume and Issue: 18(2), P. 59 - 59

Published: Jan. 22, 2025

This paper explores the overall picture regarding healthcare security systems through an extensive literature review. As sector has now become digitalized, of and, by extension, protection patient data is a key concern in modern era technological advances. Therefore, secure and integrated system essential. Thus, to evaluate relationship between quality, we conducted research identify studies reporting their association. The timeline our review based on published covering period from 2018 2024, with entries identified search relevant literature, focusing most recent developments due advances artificial intelligence algorithmic approaches. Thirty-two were included final survey. Our findings underscore critical role that significantly improve outcomes maintain integrity services. According approach, analyzed highlight growing importance advanced frameworks, especially those incorporating methodologies, safeguarding while enhancing care quality. this study, uses technology approaches, many researchers prove ransomware common threat hospital information systems, more are needed performance created against kind attack.

Language: Английский

Citations

1

Deep learning in medicine: advancing healthcare with intelligent solutions and the future of holography imaging in early diagnosis DOI
Asifa Nazir, Ahsan Hussain, Mandeep Singh

et al.

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: July 5, 2024

Language: Английский

Citations

8

A comprehensive systematic literature review of ML in nanotechnology for sustainable development DOI Creative Commons
Inam Ur Rehman, Inam Ullah, Habib Ullah Khan

et al.

Nanotechnology Reviews, Journal Year: 2024, Volume and Issue: 13(1)

Published: Jan. 1, 2024

Abstract The rapid expansion of nanotechnology has transformed numerous sectors, with nanoproducts now ubiquitous in everyday life, electronics, healthcare, and pharmaceuticals. Despite their widespread adoption, concerns persist regarding potential adverse effects, necessitating vigilant risk management. This systematic literature review advocates for leveraging artificial intelligence (AI) machine learning (ML) methodologies to enhance simulations refine safety assessments nanomaterials (NMs). Through a comprehensive examination the existing literature, this study seeks explain pivotal role AI boosting NMs sustainability efforts across six key research themes. It explores significance advancing sustainability, hazard identification, diverse applications field. In addition, it evaluates past strategies while proposing innovative avenues future exploration. By conducting analysis, aims illuminate current landscape, identify challenges, outline pathways integrating ML promote sustainable practices within nanotechnology. Furthermore, extending these technologies monitor real-world behaviour delivery. its thorough investigation, endeavours address obstacles pave way safe utilization nanotechnology, thereby minimizing associated risks.

Language: Английский

Citations

6

RFDB: Robust watermarking scheme with Fuzzy-DnCNN using blockchain technique for identity verification DOI
Divyanshu Awasthi, Priyank Khare, Vinay Kumar Srivastava

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124554 - 124554

Published: June 25, 2024

Language: Английский

Citations

4

Robust zero-watermarking method for multiple medical images using wavelet fusion and DTCWT-QR DOI

Guangyun Yang,

LU Xin-hui,

Yu Lu

et al.

Journal of Information Security and Applications, Journal Year: 2025, Volume and Issue: 90, P. 104028 - 104028

Published: March 11, 2025

Language: Английский

Citations

0

A Novel Deep Learning Zero-Watermark Method for Interior Design Protection Based on Image Fusion DOI Creative Commons
Yiran Peng, Qingqing Hu, Jing Xu

et al.

Mathematics, Journal Year: 2025, Volume and Issue: 13(6), P. 947 - 947

Published: March 13, 2025

Interior design, which integrates art and science, is vulnerable to infringements such as copying tampering. The unique often intricate nature of these designs makes them unauthorized replication misuse, posing significant challenges for designers seeking protect their intellectual property. To solve the above problems, we propose a deep learning-based zero-watermark copyright protection method. method aims embed undetectable information through image fusion technology without destroying interior design image. Specifically, fuses watermark learning generate highly robust This study also proposes verification network with U-Net verify validity extract efficiently. can accurately restore from protected images, thus effectively proving ownership work design. According on an experimental dataset, proposed in this against various image-oriented attacks. It avoids problem quality loss that traditional watermarking techniques may cause. Therefore, provide strong means field

Language: Английский

Citations

0

AI and the next medical revolution: deep learning's uncharted healthcare promise DOI

L B Krithika,

S. Vishnu,

Evans Kotei

et al.

Engineering Research Express, Journal Year: 2024, Volume and Issue: 6(2), P. 022202 - 022202

Published: June 1, 2024

Abstract Deep learning has shown tremendous potential for transforming healthcare by enabling more accurate diagnoses, improved treatment planning and better patient outcome predictions. In this comprehensive survey, we provide a detailed overview of the state-of-the-art deep techniques their applications across ecosystem. We first introduce fundamentals discuss its key advantages compared to traditional machine approaches. then present an in-depth review major in medical imaging, electronic health record analysis, genomics, robotics other domains. For each application, summarize advancements, outline technical details methods, challenges limitations highlight promising directions future work. examine cross-cutting deploying clinical settings, including interpretability, bias data scarcity. conclude proposing roadmap accelerate translation adoption high-impact learning. Overall, survey provides reference researchers practitioners working at intersection healthcare.

Language: Английский

Citations

3

Blockchain enabled MediVault for healthcare system DOI
Brijesh Kumar Chaurasia

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: June 18, 2024

Language: Английский

Citations

3