1. [Validation of segmentation techniques for positron emission tomography using ex-vivo images of oncological surgical specimens].
- Author
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Prieto E, Martí-Climent JM, Gómez-Fernández M, García-Velloso MJ, Valero M, Garrastachu P, Aristu J, Alcázar JL, Torre W, Hernández JL, Pardo FJ, Peñuelas I, and Richter JA
- Subjects
- Aged, Aged, 80 and over, Algorithms, Breast Neoplasms surgery, Colorectal Neoplasms surgery, Female, Humans, Male, Middle Aged, Prostatic Neoplasms surgery, Breast Neoplasms diagnostic imaging, Colorectal Neoplasms diagnostic imaging, Positron-Emission Tomography methods, Prostatic Neoplasms diagnostic imaging
- Abstract
Objective: To design a novel ex-vivo acquisition technique to establish a common framework to validate different segmentation techniques for oncological PET images. To evaluate several automatic segmentation algorithms on this set of images., Material and Methods: In 15 patients with cancer, ex-vivo PET studies of surgical specimens removed during surgery were performed after injection of (18)F-FDG. Images were acquired in two scanners: a clinical PET/CT and a high-resolution PET scanner. Real tumor volume was determined in each patient, and a reference image was generated for segmentation of each tumor. Images were segmented with 12 automatic algorithms and with a standard method for PET (relative threshold at 42%) and results were evaluated by quantitative parameters., Results: It has been possible to demonstrate by segmentation of PET images of surgical specimens that on high resolution PET images, 8 out of 12 evaluated segmentation techniques outperformed the standard method, whose value is 42%. However, none of the algorithms outperformed the standard method when applied on images from the clinical PET/CT. Due to the great interest of this set of PET images, all studies have been published on the Internet in order to provide a common framework for validation and comparison of different segmentation techniques., Conclusions: We have proposed a novel technique to validate segmentation techniques for oncological PET images, acquiring ex-vivo PET studies of surgical specimens. We have demonstrated the usefulness of this set of PET images by evaluating several automatic segmentation algorithms., (Copyright © 2013 Elsevier España, S.L. and SEMNIM. All rights reserved.)
- Published
- 2014
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