LEVERAGING CLOUD COMPUTING FOR TELEMEDICINE: ADVANCES IN MEDICAL IMAGE COMPRESSION, SECURITY, AND SAFETY

Ni Luh Bella Dwijaksara; Safrian Andromeda; Putri Alief Siswanto; Agrippina Waya Rahmaning Gusti; Bahar Amal; Nurani Masyita

doi:10.59003/nhj.v3i4.978

Authors

Ni Luh Bella Dwijaksara Universitas Singaperbangsa Karawang
Safrian Andromeda Universitas Singaperbangsa Karawang
Putri Alief Siswanto Institut Teknologi Sepuluh November
Agrippina Waya Rahmaning Gusti Politeknik Elektronika Negeri Surabaya
Bahar Amal Universitas Singaperbangsa Karawang
Nurani Masyita Universitas Singaperbangsa Karawang

DOI:

https://doi.org/10.59003/nhj.v3i4.978

Keywords:

Cloud Computing; Compression Techniques; Medical Image; Telemedicine; Security and Safety.

Abstract

Telemedicine has revolutionized healthcare delivery by providing remote medical consultations. This study explores the role of cloud computing in enabling telemedicine, with a particular focus on the utilization of medical image compression techniques and ensuring robust security and safety measures. The integration of cloud computing with telemedicine offers numerous advantages including scalable storage, flexible computing resources, and improved accessibility to medical data and applications. One critical aspect of telemedicine is the transmission and analysis of medical images such as X-rays, CT scans, and MRIs. However, the large size of these images can pose challenges in terms of the transmission speed and storage capacity. To address this, medical image are employed to reduce the size of images without a significant loss of diagnostic information. Security and safety are paramount in telemedicine systems, particularly when dealing with sensitive patient data and medical images. Cloud computing provides a robust infrastructure for ensuring data security and privacy, enabling the secure transmission and storage of medical images. This abstract discusses the implementation of encryption, access-control mechanisms, and authentication protocols to safeguard patient data during transmission and storage in the cloud. By leveraging cloud computing technologies, telemedicine can overcome geographical barriers and enhance healthcare accessibility for patients and healthcare professionals. Exploration of these topics will contribute to improving the efficiency, reliability, and quality of telemedicine services, ultimately leading to better patient outcomes and increased healthcare accessibility in both urban and rural settings.

Downloads

Download data is not yet available.

References

M. A. Algaet, A. S. B. H. Basari, A. A. Milad, S. M. Adrugi, and S. M. Aldeep, ‘Medical Data Compression and Transmission in Noisy WLANS: A Review’, Int. J. Grid Distrib. Comput., vol. 12, no. 2, pp. 1–18, Dec. 2019, doi: 10.33832/ijgdc.2019.12.2.01.

W.-L. Liu, K. Zhang, C. Locatis, and M. Ackerman, ‘Cloud and Traditional Videoconferencing Technology for Telemedicine and Distance Learning’, Telemed. E-Health, vol. 21, no. 5, pp. 422–426, May 2015, doi: 10.1089/tmj.2014.0121.

V. F. Rodrigues, E. P. Paim, R. Kunst, R. S. Antunes, C. A. D. Costa, and R. D. R. Righi, ‘Exploring publish/subscribe, multilevel cloud elasticity, and data compression in telemedicine’, Comput. Methods Programs Biomed., vol. 191, p. 105403, Jul. 2020, doi: 10.1016/j.cmpb.2020.105403.

Z. Jin and Y. Chen, ‘Telemedicine in the Cloud Era: Prospects and Challenges’, IEEE Pervasive Comput., vol. 14, no. 1, pp. 54–61, Jan. 2015, doi: 10.1109/MPRV.2015.19.

M. Mehrtak et al., ‘Security challenges and solutions using healthcare cloud computing’, J. Med. Life, vol. 14, no. 4, pp. 448–461, Aug. 2021, doi: 10.25122/jml-2021-0100.

A. Haleem, M. Javaid, R. P. Singh, and R. Suman, ‘Telemedicine for healthcare: Capabilities, features, barriers, and applications’, Sens. Int., vol. 2, p. 100117, 2021, doi: 10.1016/j.sintl.2021.100117.

M. Javaid, A. Haleem, R. P. Singh, S. Rab, R. Suman, and I. H. Khan, ‘Evolutionary trends in progressive cloud computing based healthcare: Ideas, enablers, and barriers’, Int. J. Cogn. Comput. Eng., vol. 3, pp. 124–135, Jun. 2022, doi: 10.1016/j.ijcce.2022.06.001.

M. J. Page et al., ‘The PRISMA 2020 statement: an updated guideline for reporting systematic reviews’, BMJ, p. n71, Mar. 2021, doi: 10.1136/bmj.n71.

H. I. Adauwiyah, M. R. Kamaluddin, R. F. Al Kautsar, and F. Fitroh, ‘Systematic Literature Review terhadap Pemanfaatan Internet of Things (IoT) dalam Bidang Kesehatan’, Appl. Inf. Syst. Manag. AISM, vol. 5, no. 2, pp. 67–74, Sep. 2022, doi: 10.15408/aism.v5i2.21187.

M. Ritonga, D. Handayani, F. Wahyuni, and I. A. Putra, ‘PELATIHAN PENGGUNAAN ZOTERO DALAM PEMBUATAN DAFTAR PUSTAKA BAGI MAHASISWA’, vol. 2, no. 1, 2023.

M. Ma, S. Fan, and D. Feng, ‘Multi-user certificateless public key encryption with conjunctive keyword search for cloud-based telemedicine’, J. Inf. Secur. Appl., vol. 55, p. 102652, Dec. 2020, doi: 10.1016/j.jisa.2020.102652.

L. Griebel et al., ‘A scoping review of cloud computing in healthcare’, BMC Med. Inform. Decis. Mak., vol. 15, no. 1, p. 17, Dec. 2015, doi: 10.1186/s12911-015-0145-7.

I. Q. Abduljaleel and A. H. Khaleel, ‘Significant medical image compression techniques: a review’, TELKOMNIKA Telecommun. Comput. Electron. Control, vol. 19, no. 5, p. 1612, Oct. 2021, doi: 10.12928/telkomnika.v19i5.18767.

C. O. Alenoghena et al., ‘Telemedicine: A Survey of Telecommunication Technologies, Developments, and Challenges’, J. Sens. Actuator Netw., vol. 12, no. 2, p. 20, Mar. 2023, doi: 10.3390/jsan12020020.

B. Calabrese and M. Cannataro, ‘Cloud Computing in Healthcare and Biomedicine’, Scalable Comput. Pract. Exp., vol. 16, no. 1, Feb. 2015, doi: 10.12694/scpe.v16i1.1057.