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Article

The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

by 1,2
1
Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Heraklion, Greece
2
Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology—Hellas (FORTH), 70013 Heraklion, Greece
Academic Editors: Leonardo Rundo, Carmelo Militello, Vincenzo Conti, Fulvio Zaccagna and Changhee Han
J. Imaging 2021, 7(8), 124; https://doi.org/10.3390/jimaging7080124
Received: 7 July 2021 / Revised: 21 July 2021 / Accepted: 22 July 2021 / Published: 23 July 2021
(This article belongs to the Special Issue Advanced Computational Methods for Oncological Image Analysis)
The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer. View Full-Text
Keywords: medical imaging; imaging biomarkers; radiomics; deep learning medical imaging; imaging biomarkers; radiomics; deep learning
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MDPI and ACS Style

Marias, K. The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics. J. Imaging 2021, 7, 124. https://doi.org/10.3390/jimaging7080124

AMA Style

Marias K. The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics. Journal of Imaging. 2021; 7(8):124. https://doi.org/10.3390/jimaging7080124

Chicago/Turabian Style

Marias, Kostas. 2021. "The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics" Journal of Imaging 7, no. 8: 124. https://doi.org/10.3390/jimaging7080124

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