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

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Design Tools and Methods in Industrial Engineering (ADM 2019)

Part of the book series: Lecture Notes in Mechanical Engineering ((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.

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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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Authors and Affiliations

  1. Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06135, Perugia, Italy

    Francesco Bianconi & Mario Luca Fravolini

  2. Section of Radiation Oncology, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132, Perugia, Italy

    Isabella Palumbo

  3. Section of Nuclear Medicine and Health Physics, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132, Perugia, Italy

    Barbara Palumbo

Authors
  1. Francesco Bianconi
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  2. Mario Luca Fravolini
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  3. Isabella Palumbo
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  4. Barbara Palumbo
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Corresponding author

Correspondence to Francesco Bianconi .

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Editors and Affiliations

  1. Dipartimento di Ingegneria Gestionale, dell‘Informazione e della Produzione, Università di Bergamo, Dalmine, Italy

    Caterina Rizzi

  2. Dipartimento Di Ingegneria “Enzo Ferrari”, Università Di Modena E Reggio Emilia, Modena, Italy

    Angelo Oreste Andrisano

  3. Dipartimento Di Ingegneria “Enzo Ferrari”, Università Di Modena E Reggio Emilia, Modena, Italy

    Francesco Leali

  4. Dipartimento Di Ingegneria “Enzo Ferrari”, Università Di Modena E Reggio Emilia, Modena, Italy

    Francesco Gherardini

  5. Dipartimento Di Ingegneria “Enzo Ferrari”, Università Di Modena E Reggio Emilia, Modena, Italy

    Fabio Pini

  6. Dipartimento Di Ingegneria “Enzo Ferrari”, Università Di Modena E Reggio Emilia, Modena, Italy

    Alberto Vergnano

Appendix: Tools and Packages for Radiomics

Appendix: Tools and Packages for Radiomics

A number of applications are already available for managing radiomics data. Among them, TexRAD (Feedback Medical Ltd, Cambridge, UK) is a commercial tool enabling lesion segmentation, feature extraction and statistical interpretation over radiomic data [55]. LIFEx (IMIV/CEA, Orsay, France) is a freeware package allowing textural analysis and radiomic feature measurements from PET, CT, ultrasound and MR images [56]. Finally, Pyradiomics (Computational Imaging & Bioinformatics Lab, Harvard Medical School, Cambridge, USA) is an open-source set of python libraries for the extraction of radiomics data from medical images as well as image loading and preprocessing [57].

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Bianconi, F., Fravolini, M.L., Palumbo, I., Palumbo, B. (2020). Shape and Texture Analysis of Radiomic Data for Computer-Assisted Diagnosis and Prognostication: An Overview. In: Rizzi, C., Andrisano, A.O., Leali, F., Gherardini, F., Pini, F., Vergnano, A. (eds) Design Tools and Methods in Industrial Engineering. ADM 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31154-4_1

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