Zobrazeno 1 - 10 of 405 pro vyhledávání: '"Shiri, Isaac"'
1
Report
Segmentation-Free Outcome Prediction in Head and Neck Cancer: Deep Learning-based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs) of PET Images
Autor: Toosi, Amirhosein, Shiri, Isaac, Zaidi, Habib, Rahmim, Arman
We introduce an innovative, simple, effective segmentation-free approach for outcome prediction in head \& neck cancer (HNC) patients. By harnessing deep learning-based feature extraction techniques and multi-angle maximum intensity projections (MA-M
Externí odkaz: http://arxiv.org/abs/2405.01756
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2
Report
Semi-supervised learning towards automated segmentation of PET images with limited annotations: Application to lymphoma patients
Autor: Yousefirizi, Fereshteh, Shiri, Isaac, O, Joo Hyun, Bloise, Ingrid, Martineau, Patrick, Wilson, Don, Bénard, François, Sehn, Laurie H., Savage, Kerry J., Zaidi, Habib, Uribe, Carlos F., Rahmim, Arman
The time-consuming task of manual segmentation challenges routine systematic quantification of disease burden. Convolutional neural networks (CNNs) hold significant promise to reliably identify locations and boundaries of tumors from PET scans. We ai
Externí odkaz: http://arxiv.org/abs/2212.09908
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3
Report
Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features
Autor: Rahmim, Arman, Toosi, Amirhosein, Salmanpour, Mohammad R., Dubljevic, Natalia, Janzen, Ian, Shiri, Isaac, Yuan, Ren, Ho, Cheryl, Zaidi, Habib, MacAulay, Calum, Uribe, Carlos, Yousefirizi, Fereshteh
Radiomics features extract quantitative information from medical images, towards the derivation of biomarkers for clinical tasks, such as diagnosis, prognosis, or treatment response assessment. Different image discretization parameters (e.g. bin numb
Externí odkaz: http://arxiv.org/abs/2203.06314
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6
Akademický článek
Segmentation-Free Outcome Prediction from Head and Neck Cancer PET/CT Images: Deep Learning-Based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs).
Autor: Toosi, Amirhosein1,2 (AUTHOR) amirhosein.toosi@ubc.ca, Shiri, Isaac3,4 (AUTHOR) habib.zaidi@unige.ch, Zaidi, Habib4 (AUTHOR), Rahmim, Arman1,2,5,6 (AUTHOR)
Publikováno v: Cancers. Jul2024, Vol. 16 Issue 14, p2538. 18p.
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