ArticleJournal of imaging2021
The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics.
Article in Journal of imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- BFMambaNet: Boundary-Frequency-Guided Global Semantic Mamba Network for Fine-GrainedPlants (Basel, Switzerland) · 2026Article
- Enhancing efficient deep learning models with multimodal, multi-teacher insights for medical image segmentation.Scientific reports · 2025Article
- A Novel 3D Magnetic Resonance Imaging Registration Framework Based on the Swin-Transformer UNet+ Model with 3D Dynamic Snake Convolution Scheme.Journal of imaging · 2025Article
- Sex Estimation Through Orbital Measurements: A Machine Learning Approach for Forensic Science.Diagnostics (Basel, Switzerland) · 2024Article
- Article
- A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images.Frontiers in neurology · 2024Review
- Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram.BMC medical imaging · 2023Article
- Osteoarthritis Diagnosis Integrating Whole Joint Radiomics and Clinical Features for Robust Learning Models Using Biological Privileged Information.Medical image computing and computer assisted intervention - MICCAI 2023 workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, proceedings · 2023Article
- Advanced Computational Methods for Oncological Image Analysis.Journal of imaging · 2021Article
Corrections and comments
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Authors and funding
1 author.
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Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.