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Shape and Texture Analysis of Radiomic Data for Computer-Assisted Diagnosis and Prognostication: An Overview

  • Francesco BianconiEmail author
  • Mario Luca Fravolini
  • Isabella Palumbo
  • Barbara Palumbo
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

There is increasing evidence that shape and texture descriptors from imaging data could be used as image biomarkers for computer-assisted diagnosis and prognostication in a number of clinical conditions. It is believed that such quantitative features may help uncover patterns that would otherwise go unnoticed to the human eye, this way offering significant advantages against traditional visual interpretation. The objective of this paper is to provide an overview of the steps involved in the process – from image acquisition to feature extraction and classification. A significant part of the work deals with the description of the most common texture and shape features used in the literature; overall issues, perspectives and directions for future research are also discussed.

Keywords

Shape Texture Radiomics Computer-assisted medicine 

Notes

Acknowledgements

This work was partially supported by the Department of Engineering at the University of Perugia, Italy, under the Fundamental Research programme 2017.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Francesco Bianconi
    • 1
    Email author
  • Mario Luca Fravolini
    • 1
  • Isabella Palumbo
    • 2
  • Barbara Palumbo
    • 3
  1. 1.Department of EngineeringUniversità degli Studi di PerugiaPerugiaItaly
  2. 2.Section of Radiation Oncology, Department of Surgical and Biomedical SciencesUniversità degli Studi di PerugiaPerugiaItaly
  3. 3.Section of Nuclear Medicine and Health Physics, Department of Surgical and Biomedical SciencesUniversità degli Studi di PerugiaPerugiaItaly

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