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REVIEW ARTICLE

Advances in image processing and pattern recognition in cancer detection, prediction, diagnosis, and prognosis

Ashok Kumar Sah1* ,  Ranjay Kumar Choudhary1 ,  Rabab H. Elshaikh1 ,  Shagun Agarwal2 ,  Manar G. Shalabi3 ,  Rajesh Prasad Jayaswal4 ,  Nurova Zarnigor Hikmatovna5 ,  Navjyot Trivedi6 ,  Khoula Salim Ali Buwaiqi7 ,  Said Al Ghenaimi8* ,  Pranav Kumar Prabhakar9 ,  Hatem Mohamed10
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1 Department of Medical Laboratory Sciences, College of Applied & Health Sciences, A’ Sharqiyah University, Ibra, North Al Sharqiyah Governorate, Oman
2 School of Allied Health Sciences, Galgotias University, Greater Noida, Uttar Pradesh, India
3 Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka, Al-Jawf Region, Saudi Arabia
4 Department of Medical Laboratory Technology, University Institute of Allied Health Sciences, Chandigarh University, Mohali, Punjab, India
5 Department of Folk Medicine, Faculty of Traditional Medicine, Bukhara State Medical Institute named after Abu Ali ibn Sino, Bukhara, Bukhara Region, Republic of Uzbekistan
6 Department of Physiotherapy, University Institute of Allied Health Sciences, Chandigarh University, Gharuan, Punjab, India
7 Research, Innovation and Technology Transfer Center, A’ Sharqiyah University, Ibra, North Al Sharqiyah Governorate, Oman
8 College of Applied and Health Sciences, A’ Sharqiyah University, Ibra, North Al Sharqiyah Governorate, Oman
9 Department of Biotechnology, School of Engineering and Technology, Nagaland University Meriema Campus, Kohima, Nagaland, India
10 Department of Counseling and Mental Health, College of Education and Arts, Lusail University, Lusail, Al Daayen, Doha, Qatar
EJMO, 025220226 https://doi.org/10.36922/EJMO025220226
Received: 29 May 2025 | Revised: 2 November 2025 | Accepted: 14 November 2025 | Published online: 1 July 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Cancer remains a global health issue, with early detection, correct diagnosis, and exact prognosis playing critical roles in improving patient outcomes. Recent developments in image processing and pattern recognition have significantly enhanced cancer detection, prediction, diagnosis, and prognosis, bridging the gap between conventional radiological methods and state-of-the-art artificial intelligence (AI)-based analytics. This review provides an in-depth introduction to the concepts, methods, and practical applications of image processing and pattern recognition in oncology. Image preprocessing algorithms, tumor segmentation algorithms, feature extraction, and pattern recognition methods based on AI, such as machine learning and deep learning models (e.g., convolutional neural networks, recurrent neural networks, and transformers), are all significant areas. We reviewed cancer prediction using radiomics, radiogenomics, AI-based histopathological diagnosis, and multimodal data fusion from imaging, genomics, and clinical history for personalized prognosis. The impact of explainable AI, 3D/4D imaging, nanotechnology-facilitated imaging, and cloud-based AI solutions is also discussed, including its impact on precision oncology and remote diagnosis. Even with these developments, significant clinical use limitations remain, including limited annotated datasets, poor interpretability, ethical considerations, and regulatory issues. This review focuses on emerging trends, including federated learning, quantum computing, and real-time AI applications, that could revolutionize cancer imaging and management. Image processing and pattern recognition, if integrated with interdisciplinary research, have the potential to develop more precise, equitable, and egalitarian cancer care in the future.

Keywords
Cancer imaging
Pattern recognition
Tumor classification
Artificial intelligence in cancer diagnosis
Multimodal data integration
Funding
None.
Conflict of interest
The authors declare no conflicts of interest.
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Eurasian Journal of Medicine and Oncology, Electronic ISSN: 2587-196X Print ISSN: 2587-2400, Published by AccScience Publishing
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