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Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation. / Zabihi, Mariam; Tangwiriyasakul, Chayanin; Ingala, Silvia; Lorenzini, Luigi; Camarasa, Robin; Barkhof, Frederik; de Bruijne, Marleen; Cardoso, M. Jorge; Sudre, Carole H.
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. ed. / Xiaohuan Cao; Xi Ouyang; Xuanang Xu; Islem Rekik; Zhiming Cui. Springer, 2024. p. 325-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14349 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
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. in X Cao, X Ouyang, X Xu, I Rekik & Z Cui (eds),
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14349 LNCS, pp. 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_33APA
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. In X. Cao, X. Ouyang, X. Xu, I. Rekik, & Z. Cui (Eds.),
Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings (pp. 325-334). Springer. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14349 LNCS
https://doi.org/10.1007/978-3-031-45676-3_33Vancouver
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. In Cao X, Ouyang X, Xu X, Rekik I, Cui Z, editors, Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Springer. 2024. p. 325-334. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14349 LNCS).
https://doi.org/10.1007/978-3-031-45676-3_33Author
Zabihi, Mariam ; Tangwiriyasakul, Chayanin ; Ingala, Silvia ; Lorenzini, Luigi ; Camarasa, Robin ; Barkhof, Frederik ; de Bruijne, Marleen ; Cardoso, M. Jorge ; Sudre, Carole H. / 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. editor / Xiaohuan Cao ; Xi Ouyang ; Xuanang Xu ; Islem Rekik ; Zhiming Cui. Springer, 2024. pp. 325-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14349 LNCS).
Bibtex
@inproceedings{0d94ac50dec143ab8f525a4d09e7ae56,
title = "Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation",
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.",
keywords = "Cerebrovascular diseases, Ellipsoid bounding shapes, enlarged perivascular spaces, Fast R-CNN",
author = "Mariam Zabihi and Chayanin Tangwiriyasakul and Silvia Ingala and Luigi Lorenzini and Robin Camarasa and Frederik Barkhof and {de Bruijne}, Marleen and Cardoso, {M. Jorge} and Sudre, {Carole H.}",
note = "Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023 ; Conference date: 08-10-2023 Through 08-10-2023",
year = "2024",
doi = "10.1007/978-3-031-45676-3_33",
language = "English",
isbn = "9783031456756",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "325--334",
editor = "Xiaohuan Cao and Xi Ouyang and Xuanang Xu and Islem Rekik and Zhiming Cui",
booktitle = "Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings",
address = "Switzerland",
}
RIS
TY - GEN
T1 - Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation
AU - Zabihi, Mariam
AU - Tangwiriyasakul, Chayanin
AU - Ingala, Silvia
AU - Lorenzini, Luigi
AU - Camarasa, Robin
AU - Barkhof, Frederik
AU - de Bruijne, Marleen
AU - Cardoso, M. Jorge
AU - Sudre, Carole H.
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Cerebrovascular diseases
KW - Ellipsoid bounding shapes
KW - enlarged perivascular spaces
KW - Fast R-CNN
U2 - 10.1007/978-3-031-45676-3_33
DO - 10.1007/978-3-031-45676-3_33
M3 - Article in proceedings
AN - SCOPUS:85175945790
SN - 9783031456756
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 325
EP - 334
BT - Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings
A2 - Cao, Xiaohuan
A2 - Ouyang, Xi
A2 - Xu, Xuanang
A2 - Rekik, Islem
A2 - Cui, Zhiming
PB - Springer
T2 - 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023
Y2 - 8 October 2023 through 8 October 2023
ER -
