Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/90497
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Duarte, Bruno | por |
dc.contributor.author | Oliveira, Bruno | por |
dc.contributor.author | Torres, Helena R. | por |
dc.contributor.author | Morais, Pedro André Gonçalves | por |
dc.contributor.author | Fonseca, Jaime C. | por |
dc.contributor.author | Vilaça, João L. | por |
dc.date.accessioned | 2024-04-03T10:52:37Z | - |
dc.date.available | 2024-04-03T10:52:37Z | - |
dc.date.issued | 2023-07 | - |
dc.identifier.citation | Duarte, B., Oliveira, B., Torres, H. R., Morais, P., Fonseca, J. C., & Vilaça, J. L. (2023, July 24). Robust 3D breast reconstruction based on monocular images and artificial intelligence for robotic guided oncological interventions. 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE. http://doi.org/10.1109/embc40787.2023.10341168 | - |
dc.identifier.isbn | 9798350324471 | por |
dc.identifier.issn | 1557-170X | - |
dc.identifier.uri | https://hdl.handle.net/1822/90497 | - |
dc.description.abstract | Breast cancer is a global public health concern. For women with suspicious breast lesions, the current diagnosis requires a biopsy, which is usually guided by ultrasound (US). However, this process is challenging due to the low quality of the US image and the complexity of dealing with the US probe and the surgical needle simultaneously, making it largely reliant on the surgeon's expertise. Some previous works employing collaborative robots emerged to improve the precision of biopsy interventions, providing an easier, safer, and more ergonomic procedure. However, for these equipment to be able to navigate around the breast autonomously, 3D breast reconstruction needs to be available. The accuracy of these systems still needs to improve, with the 3D reconstruction of the breast being one of the biggest focuses of errors. The main objective of this work is to develop a method to obtain a robust 3D reconstruction of the patient's breast, based on RGB monocular images, which later can be used to compute the robot's trajectories for the biopsy. To this end, depth estimation techniques will be developed, based on a deep learning architecture constituted by a CNN, LSTM, and MLP, to generate depth maps capable of being converted into point clouds. After merging several from multiple points of view, it is possible to generate a real-time reconstruction of the breast as a mesh. The development and validation of our method was performed using a previously described synthetic dataset. Hence, this procedure takes RGB images and the cameras' position and outputs the breasts' meshes. It has a mean error of 3.9 mm and a standard deviation of 1.2 mm. The final results attest to the ability of this methodology to predict the breast's shape and size using monocular images.Clinical Relevance - This work proposes a method based on artificial intelligence and monocular RGB images to obtain the breast's volume during robotic guided breast biopsies, improving their execution and safety. | por |
dc.description.sponsorship | EC - European Commission (CEECINST/00039/2021) | por |
dc.language.iso | eng | por |
dc.publisher | IEEE | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05549%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05549%2F2020/PT | por |
dc.relation | CEECINST/00039/2021 | por |
dc.relation | info:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F136721%2F2018/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F136670%2F2018/PT | por |
dc.rights | openAccess | por |
dc.title | Robust 3D breast reconstruction based on monocular images and artificial intelligence for robotic guided oncological interventions | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://pubmed.ncbi.nlm.nih.gov/38083333/ | por |
dc.date.updated | 2024-04-03T10:36:32Z | - |
dc.identifier.eissn | 3808-3333 | - |
dc.identifier.doi | 10.1109/EMBC40787.2023.10341168 | por |
dc.identifier.pmid | 38083333 | por |
sdum.export.identifier | 15000 | - |
sdum.journal | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | por |
sdum.conferencePublication | Annual International Conference of the IEEE Engineering in Medicine and Biology Society | por |
dc.identifier.pmc | 38083333 | - |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Robust_3D_breast_reconstruction_based_on_monocular_images_and_artificial_intelligence_for_robotic_guided_oncological_interventions.pdf | 271,4 kB | Adobe PDF | Ver/Abrir |