A survey on recent advancements for AI enabled radiomics in neuro-oncology

Syed Muhammad Anwar*, Tooba Altaf, Khola Rafique, Harish Raviprakash, Hassan Mohy-Ud-din, Ulas Bagci

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Artificial intelligence (AI) enabled radiomics has evolved immensely especially in the field of oncology. Radiomics provide assistance in diagnosis of cancer, planning of treatment strategy, and prediction of survival. Radiomics in neuro-oncology has progressed significantly in the recent past. Deep learning has outperformed conventional machine learning methods in most image-based applications. Convolutional neural networks (CNNs) have seen some popularity in radiomics, since they do not require hand-crafted features and can automatically extract features during the learning process. In this regard, it is observed that CNN based radiomics could provide state-of-the-art results in neuro-oncology, similar to the recent success of such methods in a wide spectrum of medical image analysis applications. Herein we present a review of the most recent best practices and establish the future trends for AI enabled radiomics in neuro-oncology.

Original languageEnglish (US)
Title of host publicationRadiomics and Radiogenomics in Neuro-oncology - 1st International Workshop, RNO-AI 2019, held in Conjunction with MICCAI 2019, Proceedings
EditorsHassan Mohy-ud-Din, Saima Rathore
PublisherSpringer
Pages24-35
Number of pages12
ISBN (Print)9783030401238
DOIs
StatePublished - 2020
Externally publishedYes
Event1st International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: Oct 13 2019Oct 13 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11991 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
Country/TerritoryChina
CityShenzhen
Period10/13/1910/13/19

Keywords

  • Classification
  • Deep learning
  • Neuro-oncology
  • Radiomics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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