Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Harini Veeraraghavan"'
Autor:
Jue Jiang, Chloe Min Seo Choi, Joseph O. Deasy, Andreas Rimner, Maria Thor, Harini Veeraraghavan
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 29, Iss , Pp 100542- (2024)
Background and purpose: Objective assessment of delivered radiotherapy (RT) to thoracic organs requires fast and accurate deformable dose mapping. The aim of this study was to implement and evaluate an artificial intelligence (AI) deformable image re
Externí odkaz:
https://doaj.org/article/b24784ad88214735863b6d7b3d7ac419
Autor:
Sadegh Alam, Harini Veeraraghavan, Kathryn Tringale, Emmanuel Amoateng, Ergys Subashi, Abraham J. Wu, Christopher H. Crane, Neelam Tyagi
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 21, Iss , Pp 54-61 (2022)
Background and purpose: Stereotactic body radiation therapy (SBRT) of locally advanced pancreatic cancer (LAPC) is challenging due to significant motion of gastrointestinal (GI) organs. The goal of our study was to quantify inter and intrafraction de
Externí odkaz:
https://doaj.org/article/28195363c3284ead8b5f96379707ecb5
Autor:
Maria Thor, Aditi Iyer, Jue Jiang, Aditya Apte, Harini Veeraraghavan, Natasha B. Allgood, Jennifer A. Kouri, Ying Zhou, Eve LoCastro, Sharif Elguindi, Linda Hong, Margie Hunt, Laura Cerviño, Michalis Aristophanous, Masoud Zarepisheh, Joseph O. Deasy
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 19, Iss , Pp 96-101 (2021)
Background and Purpose: Reducing trismus in radiotherapy for head and neck cancer (HNC) is important. Automated deep learning (DL) segmentation and automated planning was used to introduce new and rarely segmented masticatory structures to study if t
Externí odkaz:
https://doaj.org/article/89a0a6d630784807a792fd1a369093ab
Autor:
Harini Veeraraghavan, Claire F. Friedman, Deborah F. DeLair, Josip Ninčević, Yuki Himoto, Silvio G. Bruni, Giovanni Cappello, Iva Petkovska, Stephanie Nougaret, Ines Nikolovski, Ahmet Zehir, Nadeem R. Abu-Rustum, Carol Aghajanian, Dmitriy Zamarin, Karen A. Cadoo, Luis A. Diaz, Mario M. Leitao, Vicky Makker, Robert A. Soslow, Jennifer J. Mueller, Britta Weigelt, Yulia Lakhman
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
Abstract To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targete
Externí odkaz:
https://doaj.org/article/039f6ea3eee241349cd91ff919a41db5
Autor:
Elizabeth J. Sutton, Natsuko Onishi, Duc A. Fehr, Brittany Z. Dashevsky, Meredith Sadinski, Katja Pinker, Danny F. Martinez, Edi Brogi, Lior Braunstein, Pedram Razavi, Mahmoud El-Tamer, Virgilio Sacchini, Joseph O. Deasy, Elizabeth A. Morris, Harini Veeraraghavan
Publikováno v:
Breast Cancer Research, Vol 22, Iss 1, Pp 1-11 (2020)
Abstract Background For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develo
Externí odkaz:
https://doaj.org/article/570dbe650d5946b4ba3a963afa01ccd1
Autor:
Sharif Elguindi, Michael J. Zelefsky, Jue Jiang, Harini Veeraraghavan, Joseph O. Deasy, Margie A. Hunt, Neelam Tyagi
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 12, Iss , Pp 80-86 (2019)
Background and purpose: Magnetic resonance (MR) only radiation therapy for prostate treatment provides superior contrast for defining targets and organs-at-risk (OARs). This study aims to develop a deep learning model to leverage this advantage to au
Externí odkaz:
https://doaj.org/article/e12fdde23f9f434094d55ac4308f7012
Autor:
Natally Horvat, Harini Veeraraghavan, Caio S. R. Nahas, David D. B. Bates, Felipe R. Ferreira, Junting Zheng, Marinela Capanu, James L. Fuqua, Maria Clara Fernandes, Ramon E. Sosa, Vetri Sudar Jayaprakasam, Giovanni G. Cerri, Sergio C. Nahas, Iva Petkovska
Publikováno v:
Abdominal Radiology. 47:2770-2782
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2ea69335cf64cb9c167aef26fcdc01e
https://doi.org/10.1007/s00261-022-03572-8
https://doi.org/10.1007/s00261-022-03572-8
Publikováno v:
IEEE Transactions on Medical Imaging. 41:1057-1068
Accurate and robust segmentation of lung cancers from CT, even those located close to mediastinum, is needed to more accurately plan and deliver radiotherapy and to measure treatment response. Therefore, we developed a new cross-modality educed disti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3f7d5383b372e7c56f69203c751dc96
https://doi.org/10.1109/tmi.2021.3132291
https://doi.org/10.1109/tmi.2021.3132291
Autor:
Josiah Simeth, Jue Jiang, Anton Nosov, Andreas Wibmer, Michael Zelefsky, Neelam Tyagi, Harini Veeraraghavan
Publikováno v:
Medical Physics.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ebee5cd9034ccf127fd75767981012b
https://doi.org/10.1002/mp.16320
https://doi.org/10.1002/mp.16320
Autor:
Aditya P. Apte, Eve LoCastro, Aditi Iyer, Jue Jiang, Jung Hun Oh, Harini Veeraraghavan, Amita Shukla-Dave, Joseph O. Deasy
PurposeRecent advances in computational resources, including software libraries and hardware, have enabled the use of high-dimensional, multi-modal datasets to build Artificial Intelligence (AI) models and workflows for radiation therapy and image an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3401ec0b2ca2f105bfdefa8bbe9ea9e
https://doi.org/10.1101/2022.11.08.515686
https://doi.org/10.1101/2022.11.08.515686
