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2020 | OriginalPaper | Chapter

A Fully Automated Segmentation System of Positron Emission Tomography Studies

Authors : Albert Comelli, Alessandro Stefano

Published in: Medical Image Understanding and Analysis

Publisher: Springer International Publishing

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Abstract

In this paper, we present an automatic system for the brain metastasis delineation in Positron Emission Tomography images. The segmentation process is fully automatic, so that intervention from the user is never required making the entire process completely repeatable. Contouring is performed using an enhanced local active segmentation.

The proposed system is, at first instance, evaluated on four datasets of phantom experiments to assess the performance under different contrast ratio scenarios, and, successively, on ten clinical cases in radiotherapy environment.

Phantom studies show an excellent performance with a dice similarity coefficient rate greater than 92% for larger spheres. In clinical cases, automatically delineated tumors show high agreement with the gold standard with a dice similarity coefficient of 88.35 ± 2.60%.

These results show that the proposed system can be successfully employed in Positron Emission Tomography images, and especially in radiotherapy treatment planning, to produce fully automatic segmentations of brain cancers.

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previous chapter High-Order Markov Random Field Based Image Registration for Pulmonary CT

next chapter A General Framework for Localizing and Locally Segmenting Correlated Objects: A Case Study on Intervertebral Discs in Multi-modality MR Images

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Title: A Fully Automated Segmentation System of Positron Emission Tomography Studies
Authors: Albert Comelli
Alessandro Stefano
Publisher: Springer International Publishing
Book: Medical Image Understanding and Analysis
Print ISBN: 978-3-030-39342-7

Electronic ISBN: 978-3-030-39343-4

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-39343-4_30

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