A Review of The Applications and Challenges in Computer Vision in Medical Imaging

Raj Mehta; Mohnish Sachdeva

A Review of The Applications and Challenges in Computer Vision in Medical Imaging

November 2024

Vol-10, Issue-6

Paper ID: 25390

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Artificial Intelligence

Keywords

Computer Vision Medical Imaging Artificial Intelligence (AI) Deep Learning Image Classification Image Segmentation Anomaly Detection Explainable AI (XAI) Transfer Learning Multi-Modal Imaging Data Scarcity Model Generalization Ethical AI Healthcare Applications Clinical Integration AI Frameworks Data Privacy

Abstract

The application of computer vision in medical imaging has gained tremendous momentum over the past decade, transforming the landscape of healthcare. By leveraging advanced algorithms and AI-driven techniques, computer vision has enabled significant breakthroughs in diagnostics, treatment planning, and surgical interventions. It has streamlined the analysis of complex medical images, reduced diagnostic time and improved accuracy, ultimately contributing to better patient outcomes. From the detection of abnormalities to the segmentation of anatomical structures, the integration of AI in medical imaging has expanded the possibilities of precision medicine and personalized care. This paper explores the various applications, methodologies, and challenges associated with implementing computer vision in medical imaging. Key applications include image classification, which enables accurate diagnosis of diseases such as cancer, segmentation, which delineates critical anatomical structures for treatment planning, and anomaly detection, which aids in identifying subtle pathological changes that might otherwise go unnoticed. These techniques have shown tremendous potential in addressing healthcare challenges, particularly in areas requiring rapid and accurate image analysis. However, the integration of computer vision into medical imaging is not without challenges. Data scarcity remains a significant issue, as the development of robust AI models requires large, high-quality annotated datasets that are often difficult to obtain. Model generalization across diverse datasets and imaging conditions also presents hurdles, limiting the scalability of these solutions. Furthermore, ethical considerations such as patient data privacy and the explainability of AI decisions pose barriers to widespread adoption. This paper also discusses potential solutions to these challenges, including advancements in AI frameworks, the use of transfer learning to mitigate data constraints, and the development of explainable AI to build trust among clinicians and patients. By addressing these barriers, computer vision can revolutionize medical imaging, paving the way for a future where AI enhances every aspect of healthcare.

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Author Information

#	Name	Institute / Affiliation
1	Raj Mehta	Poornima Institute of Engineering and Technology
2	Mohnish Sachdeva	Poornima Institute of Engineering and Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

Mehta, Raj & Sachdeva, Mohnish (2024). A Review of The Applications and Challenges in Computer Vision in Medical Imaging. International Journal of Advance Research and Innovative Ideas In Education, 10(6), 1052-1060.

MLA Style

Mehta, Raj, and Mohnish Sachdeva. "A Review of The Applications and Challenges in Computer Vision in Medical Imaging." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 6, 2024, pp. 1052-1060.

IEEE Style

Raj Mehta and Mohnish Sachdeva, "A Review of The Applications and Challenges in Computer Vision in Medical Imaging," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 6, pp. 1052-1060, 2024.

Vancouver Style

Mehta Raj, Sachdeva Mohnish. A Review of The Applications and Challenges in Computer Vision in Medical Imaging. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(6):1052-1060.

Harvard Style

Mehta, Raj & Sachdeva, Mohnish (2024) 'A Review of The Applications and Challenges in Computer Vision in Medical Imaging', International Journal of Advance Research and Innovative Ideas In Education, 10(6), pp. 1052-1060.

Chicago Style

Mehta, Raj and Mohnish Sachdeva. "A Review of The Applications and Challenges in Computer Vision in Medical Imaging." International Journal of Advance Research and Innovative Ideas In Education 10, no. 6 (2024): 1052-1060.

Turabian Style

Mehta, Raj and Mohnish Sachdeva. "A Review of The Applications and Challenges in Computer Vision in Medical Imaging." International Journal of Advance Research and Innovative Ideas In Education 10, no. 6 (2024): 1052-1060.