Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation

Mariam Zabihi; Chayanin Tangwiriyasakul; Silvia Ingala; Luigi Lorenzini; Robin Camarasa; Frederik Barkhof; Marleen de Bruijne; M. Jorge Cardoso; Carole H. Sudre

doi:10.1007/978-3-031-45676-3_33

Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation

Mariam Zabihi^*, Chayanin Tangwiriyasakul, Silvia Ingala, Luigi Lorenzini, Robin Camarasa, Frederik Barkhof, Marleen de Bruijne, M. Jorge Cardoso, Carole H. Sudre

^*Corresponding author af dette arbejde

Afdeling for Røntgen og Skanning

Abstract

Enlarged perivascular spaces (EPVS) are small fluid-filled spaces surrounding blood vessels in the brain. They have been found to be important in the development and progression of cerebrovascular disease, including stroke, dementia, and cerebral small vessel disease. Their accurate detection and quantification are crucial for early diagnosis and better management of these diseases. In recent years, object detection techniques such as Mask R-CNN approach have been widely used to automate the detection and segmentation of small objects. To account for the tubular shape of these markers we use ellipsoid shapes instead of bounding boxes to express the location of individual elements in the implementation of the Fast R-CNN. We investigate the performance of this model under different modality combinations and find that the T2 modality alone, as well as the combination of T1+T2, deliver better performance.

Originalsprog	Engelsk
Titel	Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings
Redaktører	Xiaohuan Cao, Xi Ouyang, Xuanang Xu, Islem Rekik, Zhiming Cui
Antal sider	10
Forlag	Springer Science and Business Media Deutschland GmbH
Publikationsdato	2024
Sider	325-334
ISBN (Trykt)	9783031456756
DOI	https://doi.org/10.1007/978-3-031-45676-3_33
Status	Udgivet - 2024
Begivenhed	14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023 - Vancouver, Canada Varighed: 8 okt. 2023 → 8 okt. 2023

Konference

Konference	14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023
Land/Område	Canada
By	Vancouver
Periode	08/10/2023 → 08/10/2023

Navn	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind	14349 LNCS
ISSN	0302-9743

Adgang til dokumentet

10.1007/978-3-031-45676-3_33

Andre filer og links

Link to publication in Scopus

Citationsformater

Zabihi, M., Tangwiriyasakul, C., Ingala, S., Lorenzini, L., Camarasa, R., Barkhof, F., de Bruijne, M., Cardoso, M. J., & Sudre, C. H. (2024). Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. I X. Cao, X. Ouyang, X. Xu, I. Rekik, & Z. Cui (red.), Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings (s. 325-334). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-45676-3_33

Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. / Zabihi, Mariam; Tangwiriyasakul, Chayanin; Ingala, Silvia et al.
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. red. / Xiaohuan Cao; Xi Ouyang; Xuanang Xu; Islem Rekik; Zhiming Cui. Springer Science and Business Media Deutschland GmbH, 2024. s. 325-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14349 LNCS).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Zabihi, M, Tangwiriyasakul, C, Ingala, S, Lorenzini, L, Camarasa, R, Barkhof, F, de Bruijne, M, Cardoso, MJ & Sudre, CH 2024, Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. i X Cao, X Ouyang, X Xu, I Rekik & Z Cui (red), Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Springer Science and Business Media Deutschland GmbH, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), bind 14349 LNCS, s. 325-334, 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, Vancouver, Canada, 08/10/2023. https://doi.org/10.1007/978-3-031-45676-3_33

Zabihi M, Tangwiriyasakul C, Ingala S, Lorenzini L, Camarasa R, Barkhof F et al. Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. I Cao X, Ouyang X, Xu X, Rekik I, Cui Z, red., Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. s. 325-334. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14349 LNCS). doi: 10.1007/978-3-031-45676-3_33

Zabihi, Mariam ; Tangwiriyasakul, Chayanin ; Ingala, Silvia et al. / Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. red. / Xiaohuan Cao ; Xi Ouyang ; Xuanang Xu ; Islem Rekik ; Zhiming Cui. Springer Science and Business Media Deutschland GmbH, 2024. s. 325-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14349 LNCS).

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