Biomedical Imaging Technologies: A Comparative Study of MRI, CT, and Ultrasound Innovations

  • Vikram Singh B.Tech Final Year Student, Department of Instrumentation and Control, Indian Institute of Technology (IIT) Indore, India

Abstract

Biomedical imaging plays a crucial role in modern healthcare, offering non-invasive techniques for diagnosing, monitoring, and guiding treatments for various medical conditions. Advanced imaging technologies have significantly transformed clinical decision-making, enabling early disease detection and precise treatment planning. Among the most widely used imaging modalities, Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Ultrasound (US) stand out due to their diverse applications across multiple medical fields.


MRI is known for its high soft-tissue contrast and radiation-free imaging, making it ideal for neurological, musculoskeletal, and oncological applications. CT provides rapid, high-resolution cross-sectional imaging, making it invaluable for emergency diagnostics, trauma assessment, and vascular imaging. Ultrasound, being portable, cost-effective, and real-time, is extensively used in obstetrics, cardiology, and point-of-care diagnostics.


Recent innovations in biomedical imaging focus on enhancing resolution, speed, and accuracy while minimizing risks such as radiation exposure and scan-related artifacts. Advances such as AI-powered image reconstruction, photon-counting CT, elastography, and functional MRI (fMRI) are pushing the boundaries of imaging capabilities. Additionally, the integration of machine learning, deep learning algorithms, and hybrid imaging techniques (such as PET-MRI and CT-MRI) is revolutionizing image processing, analysis, and disease prediction.


This review provides a comparative analysis of MRI, CT, and ultrasound, discussing their fundamental principles, clinical applications, benefits, and challenges. Furthermore, we explore the latest developments in contrast agents, AI-driven automation, and wearable imaging technologies, highlighting their potential to improve patient outcomes and advance precision medicine. The continuous evolution of biomedical imaging is shaping the future of healthcare, promising faster, safer, and more accurate diagnostic solutions for a wide range of medical conditions.

References

1. McRobbie DW, Moore EA, Graves MJ, Prince MR. MRI from Picture to Proton. Cambridge university press;
2017 Apr 13.
2. Bushberg JT, Boone JM. The essential physics of medical imaging. Lippincott Williams & Wilkins; 2011 Dec 20.
3. Rinck PA. Magnetic resonance in medicine: a critical introduction. BoD–Books on Demand; 2018 Aug 21.
4. Kalender WA. Computed tomography: fundamentals, system technology, image quality, applications. John
Wiley & Sons; 2011 Jul 7.
5. Webb A. Introduction to biomedical imaging. John Wiley & Sons; 2022 Oct 19.
6. Buzug TM. Computed tomography: from photon statistics to modern cone-beam CT. Soc Nuclear Med.
2009 Jul;50(7).
7. Yitbarek D, Dagnaw GG. Application of advanced imaging modalities in veterinary medicine: a review.
Veterinary Medicine: Research and Reports. 2022 May 31:117-30.
8. Roemer PB, Edelstein WA, Hayes CE, Souza SP, Mueller OM. The NMR phased array. Magnetic resonance in
medicine. 1990 Nov;16(2):192-225.
9. Gebhard C, Fiechter M, Fuchs TA, Ghadri JR, Herzog BA, Kuhn F, Stehli J, Müller E, Kazakauskaite E, Gaemperli
O, Kaufmann PA. Coronary artery calcium scoring: influence of adaptive statistical iterative reconstruction
using 64-MDCT. International journal of cardiology. 2013 Sep 10;167(6):2932-7.
10. Giger ML, Chan HP, Boone J. Anniversary paper: history and status of CAD and quantitative image analysis: the role of medical physics and AAPM. Medical physics. 2008 Dec;35(12):5799-820.
11. Alyousef K, Assiri A, Almutairi S, Aldalham T, Felimban G. Awareness of radiation protection and common
radiation dose levels among healthcare workers. Global journal on quality and safety in healthcare. 2023 Feb 1;6(1):1-5.
12. O’connor JP, Aboagye EO, Adams JE, Aerts HJ, Barrington SF, Beer AJ, Boellaard R, Bohndiek SE, Brady
M, Brown G, Buckley DL. Imaging biomarker roadmap for cancer studies. Nature reviews Clinical oncology.
2017 Mar;14(3):169-86.
13. Brau AC, Hardy CJ, Schenck JF. MRI safety. InBasic Principles of Cardiovascular MRI: Physics and Imaging
Technique 2015 Oct 29 (pp. 115-127). Cham: Springer International Publishing.
14. Fütterer JJ, Briganti A, De Visschere P, Emberton M, Giannarini G, Kirkham A, Taneja SS, Thoeny H, Villeirs
G, Villers A. Can clinically significant prostate cancer be detected with multiparametric magnetic resonance
imaging? A systematic review of the literature. European urology. 2015 Dec 1;68(6):1045-53.
15. Liu X, Song L, Liu S, Zhang Y. A review of deeplearning-based medical image segmentation methods.
Sustainability. 2021 Jan 25;13(3):1224.
16. Lu G, Fei B. Medical hyperspectral imaging: a review. Journal of biomedical optics. 2014 Jan 1;19(1):010901-.
17. Kahn Jr CE, Langlotz CP, Burnside ES, Carrino JA, Channin DS, Hovsepian DM, Rubin DL. Toward best practices in radiology reporting. Radiology. 2009 Sep;252(3):852-6.
18. Rubin GD. Computed tomography: revolutionizing the practice of medicine for 40 years. Radiology. 2014
Nov;273(2S):S45-74.
Published
2025-05-03
How to Cite
SINGH, Vikram. Biomedical Imaging Technologies: A Comparative Study of MRI, CT, and Ultrasound Innovations. Journal of Advanced Research in Instrumentation and Control Engineering, [S.l.], v. 12, n. 1&2, p. 11-17, may 2025. ISSN 2456-1398. Available at: <http://www.thejournalshouse.com/index.php/instrumentation-control-engg-adr/article/view/1435>. Date accessed: 04 may 2025.