skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges

Theranostics, 2019-01, Vol.9 (5), p.1303-1322 [Peer Reviewed Journal]

Ivyspring International Publisher 2019 ;ISSN: 1838-7640 ;EISSN: 1838-7640 ;DOI: 10.7150/thno.30309 ;PMID: 30867832

Full text available

Citations Cited by
  • Title:
    The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges
  • Author: Liu, Zhenyu ; Wang, Shuo ; Dong, Di ; Wei, Jingwei ; Fang, Cheng ; Zhou, Xuezhi ; Sun, Kai ; Li, Longfei ; Li, Bo ; Wang, Meiyun ; Tian, Jie
  • Subjects: Diagnostic Imaging - methods ; Diagnostic Imaging - trends ; Humans ; Image Processing, Computer-Assisted - methods ; Image Processing, Computer-Assisted - trends ; Neoplasms - diagnostic imaging ; Precision Medicine - methods ; Precision Medicine - trends ; Radiography - methods ; Radiography - trends ; Review
  • Is Part Of: Theranostics, 2019-01, Vol.9 (5), p.1303-1322
  • Description: Medical imaging can assess the tumor and its environment in their entirety, which makes it suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in computational methods, especially in artificial intelligence for medical image process and analysis, has converted these images into quantitative and minable data associated with clinical events in oncology management. This concept was first described as radiomics in 2012. Since then, computer scientists, radiologists, and oncologists have gravitated towards this new tool and exploited advanced methodologies to mine the information behind medical images. On the basis of a great quantity of radiographic images and novel computational technologies, researchers developed and validated radiomic models that may improve the accuracy of diagnoses and therapy response assessments. Here, we review the recent methodological developments in radiomics, including data acquisition, tumor segmentation, feature extraction, and modelling, as well as the rapidly developing deep learning technology. Moreover, we outline the main applications of radiomics in diagnosis, treatment planning and evaluations in the field of oncology with the aim of developing quantitative and personalized medicine. Finally, we discuss the challenges in the field of radiomics and the scope and clinical applicability of these methods.
  • Publisher: Australia: Ivyspring International Publisher
  • Language: English
  • Identifier: ISSN: 1838-7640
    EISSN: 1838-7640
    DOI: 10.7150/thno.30309
    PMID: 30867832
  • Source: MEDLINE
    PubMed Central
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central

Searching Remote Databases, Please Wait