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François Bénard
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2020 – today
- 2024
- [c4]Amirhosein Toosi
, Sara Harsini
How to Segment in 3D Using 2D Models: Automated 3D Segmentation of Prostate Cancer Metastatic Lesions on PET Volumes Using Multi-angle Maximum Intensity Projections and Diffusion Models. DGM4MICCAI@MICCAI 2024: 212-221 - [i2]Amirhosein Toosi, Sara Harsini, François Bénard, Carlos F. Uribe, Arman Rahmim:
How To Segment in 3D Using 2D Models: Automated 3D Segmentation of Prostate Cancer Metastatic Lesions on PET Volumes Using Multi-Angle Maximum Intensity Projections and Diffusion Models. CoRR abs/2407.18555 (2024) - 2023
- [j2]Yixi Xu
Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss. Comput. Biol. Medicine 158: 106882 (2023) - [c3]Amirhosein Toosi, Sara Harsini
State-of-the-art object detection algorithms for small lesion detection in PSMA PET: use of rotational maximum intensity projection (MIP) images. Image Processing 2023 - [i1]Shadab Ahamed, Yixi Xu, Claire Gowdy, Joo Hyun O, Ingrid Bloise, Don Wilson, Patrick Martineau, François Bénard, Fereshteh Yousefirizi, Rahul Dodhia, Juan M. Lavista Ferres, William B. Weeks, Carlos F. Uribe, Arman Rahmim:
Comprehensive Evaluation and Insights into the Use of Deep Neural Networks to Detect and Quantify Lymphoma Lesions in PET/CT Images. CoRR abs/2311.09614 (2023)
2010 – 2019
- 2018
- [j1]Saeid Asgari Taghanaki
Segmentation-free direct tumor volume and metabolic activity estimation from PET scans. Comput. Medical Imaging Graph. 63: 52-66 (2018) - 2017
- [c2]Jesse Tanguay, François Bénard, Anna Celler, Thomas Ruth, Paul Schaffer:
Spatial resolution properties of digital autoradiography systems for pre-clinical alpha particle imaging (Conference Presentation). Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 1013716 - 2016
- [c1]Payam Ahmadvand
Tumor Lesion Segmentation from 3D PET Using a Machine Learning Driven Active Surface. MLMI@MICCAI 2016: 271-278
Coauthor Index
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last updated on 2024-11-28 20:29 CET by the dblp team
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