Výsledky vyhledávání - "Lisanne Van Dijk"

Akademický článek

Comparison of Machine-Learning and Deep-Learning Methods for the Prediction of Osteoradionecrosis Resulting From Head and Neck Cancer Radiation Therapy

Autor: Brandon Reber, BS, Lisanne Van Dijk, PhD, Brian Anderson, PhD, Abdallah Sherif Radwan Mohamed, MD, PhD, Clifton Fuller, MD, PhD, Stephen Lai, MD, PhD, Kristy Brock, PhD

Publikováno v: Advances in Radiation Oncology, Vol 8, Iss 4, Pp 101163- (2023)

Purpose: Deep-learning (DL) techniques have been successful in disease-prediction tasks and could improve the prediction of mandible osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiation therapy. In this study, we retrospective

Externí odkaz: https://doaj.org/article/8de3d5b32ac343cca629c88b5409c8d8

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Akademický článek

Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad

Autor: Elisa Tardini, Xinhua Zhang, Guadalupe Canahuate, Andrew Wentzel, Abdallah S R Mohamed, Lisanne Van Dijk, Clifton D Fuller, G Elisabeta Marai

Publikováno v: Journal of Medical Internet Research, Vol 24, Iss 4, p e29455 (2022)

BackgroundCurrently, selection of patients for sequential versus concurrent chemotherapy and radiation regimens lacks evidentiary support and it is based on locally optimal decisions for each step. ObjectiveWe aim to optimize the multistep treatment

Externí odkaz: https://doaj.org/article/5aa6204b28304a3c880f1292edd629f0

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Emergent anisotropy and textures in two dimensional magnetic arrays

Autor: Nanny Strandqvist, Björn Erik Skovdal, Merlin Pohlit, Henry Stopfel, Lisanne van Dijk, Vassilios Kapaklis, Björgvin Hjörvarsson

Publikováno v: Physical Review Materials. 6

We demonstrate the presence of an emergent magnetic anisotropy in square lattices of circular mesospins. An external field is used to saturate the magnetization along the [10] and [11] directions before quantifying the magnetic textures at remanence.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3d969f98169919072ec506346ca2f3f
https://doi.org/10.1103/physrevmaterials.6.105201

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Head and Neck Cancer Primary Tumor Auto Segmentation Using Model Ensembling of Deep Learning in PET/CT Images

Autor: Mohamed Naser, Moamen Abobakr Abdelaal, Renjie He, Kareem Wahid, Lisanne Van Dijk, Clifton Fuller, Cem Dede, Abdallah Mohamed

Publikováno v: Head Neck Tumor Segm Chall (2021)
Lecture Notes in Computer Science ISBN: 9783030982522

Auto-segmentation of primary tumors in oropharyngeal cancer using PET/CT images is an unmet need that has the potential to improve radiation oncology workflows. In this study, we develop a series of deep learning models based on a 3D Residual Unet (R

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2e54552eec30f1b9dbc09488bf785c7
https://pubmed.ncbi.nlm.nih.gov/35399869

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MR-Guided Adaptive Radiotherapy for OAR Sparing in Head and Neck Cancers

Autor: Samuel L. Mulder, Jolien Heukelom, Brigid A. McDonald, Lisanne Van Dijk, Kareem A. Wahid, Keith Sanders, Travis C. Salzillo, Mehdi Hemmati, Andrew Schaefer, Clifton D. Fuller

Publikováno v: Cancers. 14(8)

MR-linac devices offer the potential for advancements in radiotherapy (RT) treatment of head and neck cancer (HNC) by using daily MR imaging performed at the time and setup of treatment delivery. This article aims to present a review of current adapt

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efa2e33d5b375bcf9b7e33930753b2a3
https://pubmed.ncbi.nlm.nih.gov/35454816

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Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma

Autor: Mohamed Naser, Moamen Abobakr Abdelaal, Renjie He, Kareem Wahid, Lisanne Van Dijk, Clifton Fuller, Cem Dede, Abdallah Mohamed

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030982522
Head Neck Tumor Segm Chall (2021)

PET/CT images provide a rich data source for clinical prediction models in head and neck squamous cell carcinoma (HNSCC). Deep learning models often use images in an end-to-end fashion with clinical data or no additional input for predictions. Howeve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3d5ad299fc4496ace15a575c676f00a
https://doi.org/10.1007/978-3-030-98253-9_28

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Progression Free Survival Prediction for Head and Neck Cancer Using Deep Learning Based on Clinical and PET/CT Imaging Data

Autor: Mohamed Naser, Moamen Abobakr Abdelaal, Renjie He, Kareem Wahid, Lisanne Van Dijk, Clifton Fuller, Cem Dede, Abdallah Mohamed

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030982522
Head Neck Tumor Segm Chall (2021)

Determining progression-free survival (PFS) for head and neck squamous cell carcinoma (HNSCC) patients is a challenging but pertinent task that could help stratify patients for improved overall outcomes. PET/CT images provide a rich source of anatomi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de978315f5e9b2a98775c185461a60d6
https://doi.org/10.1007/978-3-030-98253-9_27

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Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images

Autor: Johannes A. Langendijk, Nanna Maria Sijtsema, Alessia De Biase, Lisanne Van Dijk, Peter Van Ooijen

Publikováno v: Physics in Medicine and Biology, 68(5). IOP PUBLISHING LTD

Objective. Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oropharyngeal cancer patients (OPC) each image volume is explored slice-by-slice from different

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83a8fdd3177a3c3c61fa1d1bc2d45a4e
https://doi.org/10.1088/1361-6560/acb9cf

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Optimal Treatment Selection in Sequential Systemic and Locoregional Therapy of Oropharyngeal Squamous Carcinomas: Deep Q-Learning With a Patient-Physician Digital Twin Dyad (Preprint)

Autor: Elisa Tardini, Xinhua Zhang, Guadalupe Canahuate, Andrew Wentzel, Abdallah S R Mohamed, Lisanne Van Dijk, Clifton D Fuller, G Elisabeta Marai

BACKGROUND Currently, selection of patients for sequential versus concurrent chemotherapy and radiation regimens lacks evidentiary support and it is based on locally optimal decisions for each step. OBJECTIVE We aim to optimize the multistep treatmen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::68fb355befca3c28fd3a95eb79430868
https://doi.org/10.2196/preprints.29455

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Normal Tissue Complication Probability (NTCP) prediction model for osteoradionecrosis of the mandible in head and neck cancer patients following radiotherapy: Large-scale observational cohort

Autor: Mohamed Naser, Jillian Rigert, Katherine Hutcheson, Lisanne Van Dijk, Clifton Fuller, Abdelrahman Abusaif, Stephen Lai, Abdallah Mohamed

Background and purposeOsteoradionecrosis (ORN) of the mandible represents a severe, debilitating complication of radiation therapy (RT) for head and neck cancer (HNC). At present, no Normal Tissue Complication Probability (NTCP) models for risk of OR

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c9862eccf40efde710b2ea880d8dfc9f
https://doi.org/10.1101/2021.03.04.21252505

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