Multiparametric magnetic resonance imaging (mpMRI) is emerging as a promising tool in the clinical pathway of prostate cancer (PCa). The registration between a structural and a functional imaging modality, such as T2-weighted (T2w) and diffusion-weighted imaging (DWI) is fundamental in the development of a mpMRI-based computer aided diagnosis (CAD) system for PCa. Here, we propose an automated method to register the prostate gland in T2w and DWI image sequences by a landmark-based affine registration and a non-parametric diffeomorphic registration. An expert operator manually segmented the prostate gland in both modalities on a dataset of 20 patients. Target registration error and Jaccard index, which measures the overlap between masks, were evaluated pre-and post-registration resulting in an improvement of 44% and 21%, respectively. In the future, the proposed method could be useful in the framework of a CAD system for PCa detection and characterization in mpMRI.
Multimodal T2w and DWI Prostate Gland Automated Registration / De Santi, B.; Salvi, M.; Giannini, V.; Meiburger, K. M.; Michielli, N.; Seoni, S.; Regge, D.; Molinari, F.. - ELETTRONICO. - 2019(2019), pp. 4427-4430. ((Intervento presentato al convegno 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 tenutosi a deu nel 2019 [10.1109/EMBC.2019.8856467].
Titolo: | Multimodal T2w and DWI Prostate Gland Automated Registration | |
Autori: | ||
Data di pubblicazione: | 2019 | |
Serie: | ||
Abstract: | Multiparametric magnetic resonance imaging (mpMRI) is emerging as a promising tool in the clinica...l pathway of prostate cancer (PCa). The registration between a structural and a functional imaging modality, such as T2-weighted (T2w) and diffusion-weighted imaging (DWI) is fundamental in the development of a mpMRI-based computer aided diagnosis (CAD) system for PCa. Here, we propose an automated method to register the prostate gland in T2w and DWI image sequences by a landmark-based affine registration and a non-parametric diffeomorphic registration. An expert operator manually segmented the prostate gland in both modalities on a dataset of 20 patients. Target registration error and Jaccard index, which measures the overlap between masks, were evaluated pre-and post-registration resulting in an improvement of 44% and 21%, respectively. In the future, the proposed method could be useful in the framework of a CAD system for PCa detection and characterization in mpMRI. | |
ISBN: | 978-1-5386-1311-5 | |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11583/2872998