Classification of methods for generating pseudo-CT from MRI images for MRI-alone RT
Journal Title: UNKNOWN - Year 2017, Vol 1, Issue 3
Abstract
Background: Since the last decades, research have been oriented towards an MRI-alone radiation treatment planning (RTP), where MRI is used as the primary modality for imaging, delineation and dose calculation by assigning to it the needed electron density (ED) information. The idea is to create a computed tomography (CT) image or so-called pseudo-CT from MRI data. In this paper, we review and classify methods for creating pseudo-CT images from MRI data. Each class of methods is explained and a group of works in the literature is presented in detail with statistical performance. We discuss the advantages, drawbacks and limitations of each class of methods. Methods: We classified most recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods. We based the classification on the general technique applied in the approach. Results: Most of research focused on the brain and the pelvis regions. The mean absolute error (MAE) ranged from 80 HU to 137 HU and from 36.4 HU to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy field is emerging towards the generalization of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images. However, a benchmark is needed to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method.
Authors and Affiliations
Wafa BOUKELLOUZ, Abdelouahab MOUSSAOUI
Keywords
Related Articles
- EP ID EP261248
- DOI 10.26415/2572-004X-vol1iss3p54-54
- Views 42
- Downloads 0
The new design of a remote real time embedded medical platform
Background: The aim of this work is to develop an electronic medical platform that enables us to monitor the physiological data of a patient and allows in cases of urgent problems to trigger an alarm remotely controlled...
Real-time sleep apnea detection using wavelet packet transform and support vector machines
Sleep apnea events as obstructive, central, mixed, or hypopnea are characterized by frequent breathing cessations or reduction in upper airflow during sleep. An advanced method for analyzing the patterning of biomedical...
Modeling collaborative learning: case of clinical reasoning
Background: Collaborative learning is an important pedagogical strategy which gained a huge interest in critical domains such as the medical field. However, to ensure the quality of this learning method, it is necessary...
Involvement of the AT1 Receptor in the Pathophysiology of the Respiratory Failure Induced by Scorpion Venom
Background: Renin-Angiotensin System (RAS) is related to cardiovascular diseases. It is also involved in the pathogenesis of pulmonary dysfunction, through the induction of proinflammatory mediators in lungs. Respirator...
Algorithmic processing to aid in leukemia detection
Background: I present our medical context with some basic concepts in order to understand the results of our work, and then I begin the explanation of mathematical morphology. I will conclude by the description of algori...