Maria Ciolina1, Balaji Ganeshan2, Andrea Laghi1
1 Department of Radiological Sciences, Oncology and Pathology, Sapienza – University of Rome, Polo Pontino, Latina, Italy
2 Institute of Nuclear Medicine, University College London, United Kingdom
Introduction
Texture analysis is an image-processing algorithm that can be used to quantify tissue heterogeneity based on the distribution of pixel gray-level intensity, coarseness and regularity within an image. Texture analysis was first introduced to medical imaging in 1973, when it was applied to radiographs and, subsequently, to ultrasound (reviewed in [1]). Only recently has it found new applications in oncologic imaging (e.g. CT, PET, MRI, mammography) where texture is emerging as a possible imaging biomarker, to assess the heterogeneity within a tumor. This essay provides a brief overview of the methodological aspects and clinical utility of texture analysis in oncology.