Abstract
It is well known that some sort of motion correction technique (MCT) should be performed before DCE-MRI data analysis in order to reduce movement artefacts. However, it is not clear if a single MCT can produce optimum results for every single examination, since for example different movements can occur. In this paper we investigated the possibility of choosing the best MCT per each specific patient, before performing further data analysis (e.g. tumour segmentation). In particular, our aim is the proposal of some physiological model-based quality indexes (QIs) for ranking different MCT on a patient basis. Moreover, for practical feasibility, we investigated the performance of our proposal when only a small fraction of the available data was used. We performed tests on a dataset of patients with breast tumour. Specifically, for each patient we compared the 'reference ranking' of different MCT obtained by using the results of tumour segmentation with the rankings produced with each QI. Our results indicate that the ranking obtained by using the QI based on the Extended Tofts-Kermode model (with the Parker arterial input function) are in accordance with the 'reference ranking'. Moreover, computational load can be significantly reduced without affecting the overall performance by using only 5% of the available data.
| Original language | English |
|---|---|
| Title of host publication | 2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 273-278 |
| Number of pages | 6 |
| ISBN (Print) | 9781479964765 |
| DOIs | |
| Publication status | Published - Jun 30 2015 |
| Event | 2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Torino, Italy Duration: May 7 2015 → May 9 2015 |
Other
| Other | 2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 |
|---|---|
| Country | Italy |
| City | Torino |
| Period | 5/7/15 → 5/9/15 |
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Keywords
- DCE-MRI
- Extended Tofts Model
- Hyton-Brady Model
- Image Registration
- Motion Correction
- Quality Index
- Tofts Model
ASJC Scopus subject areas
- Biomedical Engineering
- Computer Science Applications
Cite this
Data-driven selection of motion correction techniques in breast DCE-MRI. / Piantadosi, Gabriele; Marrone, Stefano; Fusco, Roberta; Petrillo, Antonella; Sansone, Mario; Sansone, Carlo.
2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 273-278 7145212.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Data-driven selection of motion correction techniques in breast DCE-MRI
AU - Piantadosi, Gabriele
AU - Marrone, Stefano
AU - Fusco, Roberta
AU - Petrillo, Antonella
AU - Sansone, Mario
AU - Sansone, Carlo
PY - 2015/6/30
Y1 - 2015/6/30
N2 - It is well known that some sort of motion correction technique (MCT) should be performed before DCE-MRI data analysis in order to reduce movement artefacts. However, it is not clear if a single MCT can produce optimum results for every single examination, since for example different movements can occur. In this paper we investigated the possibility of choosing the best MCT per each specific patient, before performing further data analysis (e.g. tumour segmentation). In particular, our aim is the proposal of some physiological model-based quality indexes (QIs) for ranking different MCT on a patient basis. Moreover, for practical feasibility, we investigated the performance of our proposal when only a small fraction of the available data was used. We performed tests on a dataset of patients with breast tumour. Specifically, for each patient we compared the 'reference ranking' of different MCT obtained by using the results of tumour segmentation with the rankings produced with each QI. Our results indicate that the ranking obtained by using the QI based on the Extended Tofts-Kermode model (with the Parker arterial input function) are in accordance with the 'reference ranking'. Moreover, computational load can be significantly reduced without affecting the overall performance by using only 5% of the available data.
AB - It is well known that some sort of motion correction technique (MCT) should be performed before DCE-MRI data analysis in order to reduce movement artefacts. However, it is not clear if a single MCT can produce optimum results for every single examination, since for example different movements can occur. In this paper we investigated the possibility of choosing the best MCT per each specific patient, before performing further data analysis (e.g. tumour segmentation). In particular, our aim is the proposal of some physiological model-based quality indexes (QIs) for ranking different MCT on a patient basis. Moreover, for practical feasibility, we investigated the performance of our proposal when only a small fraction of the available data was used. We performed tests on a dataset of patients with breast tumour. Specifically, for each patient we compared the 'reference ranking' of different MCT obtained by using the results of tumour segmentation with the rankings produced with each QI. Our results indicate that the ranking obtained by using the QI based on the Extended Tofts-Kermode model (with the Parker arterial input function) are in accordance with the 'reference ranking'. Moreover, computational load can be significantly reduced without affecting the overall performance by using only 5% of the available data.
KW - DCE-MRI
KW - Extended Tofts Model
KW - Hyton-Brady Model
KW - Image Registration
KW - Motion Correction
KW - Quality Index
KW - Tofts Model
UR - http://www.scopus.com/inward/record.url?scp=84939493669&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84939493669&partnerID=8YFLogxK
U2 - 10.1109/MeMeA.2015.7145212
DO - 10.1109/MeMeA.2015.7145212
M3 - Conference contribution
AN - SCOPUS:84939493669
SN - 9781479964765
SP - 273
EP - 278
BT - 2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -