Výsledky vyhledávání - "Wilson, Don P"

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A cascaded deep network for automated tumor detection and segmentation in clinical PET imaging of diffuse large B-cell lymphoma

Autor: Ahamed, Shadab, Dubljevic, Natalia, Bloise, Ingrid, Gowdy, Claire, Martineau, Patrick, Wilson, Don, Uribe, Carlos F., Rahmim, Arman, Yousefirizi, Fereshteh

Publikováno v: Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 120323M (4 April 2022)

Accurate detection and segmentation of diffuse large B-cell lymphoma (DLBCL) from PET images has important implications for estimation of total metabolic tumor volume, radiomics analysis, surgical intervention and radiotherapy. Manual segmentation of

Externí odkaz: http://arxiv.org/abs/2403.07092

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Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses

Autor: Ahamed, Shadab, Xu, Yixi, Kurkowska, Sara, Gowdy, Claire, O, Joo H., Bloise, Ingrid, Wilson, Don, Martineau, Patrick, Bénard, François, Yousefirizi, Fereshteh, Dodhia, Rahul, Lavista, Juan M., Weeks, William B., Uribe, Carlos F., Rahmim, Arman

This study addresses critical gaps in automated lymphoma segmentation from PET/CT images, focusing on issues often overlooked in existing literature. While deep learning has been applied for lymphoma lesion segmentation, few studies incorporate out-o

Externí odkaz: http://arxiv.org/abs/2311.09614

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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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Convolutional neural network with a hybrid loss function for fully automated segmentation of lymphoma lesions in FDG PET images

Autor: Yousefirizi, Fereshteh, Dubljevic, Natalia, Ahamed, Shadab, Bloise, Ingrid, Gowdy, Claire, O, Joo Hyun, Farag, Youssef, de Schaetzen, Rodrigue, Martineau, Patrick, Wilson, Don, Uribe, Carlos F., Rahmim, Arman

Segmentation of lymphoma lesions is challenging due to their varied sizes and locations in whole-body PET scans. This work presents a fully-automated segmentation technique using a multi-center dataset of diffuse large B-cell lymphoma (DLBCL) with he

Externí odkaz: http://arxiv.org/abs/2208.00274

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