Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Azar Sadeghnejad Barkousaraie"'
Autor:
Maryam Mashayekhi, Itzel Ramirez Tapia, Anjali Balagopal, Xinran Zhong, Azar Sadeghnejad Barkousaraie, Rafe McBeth, Mu‐Han Lin, Steve Jiang, Dan Nguyen
Publikováno v:
Med Phys
PURPOSE: Typically, the current dose prediction models are limited to small amounts of data and require re-training for a specific site, often leading to suboptimal performance. We propose a site-agnostic, three dimensional dose distribution predicti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49ad655d0add0ff97ebfde3da080666f
https://europepmc.org/articles/PMC9870295/
https://europepmc.org/articles/PMC9870295/
Autor:
Rafe McBeth, Steve B. Jiang, Anjali Balagopal, Gyanendra Bohara, Mu-Han Lin, Dan Nguyen, Azar Sadeghnejad Barkousaraie
Publikováno v:
Phys Med Biol
Recently, artificial intelligence technologies and algorithms have become a major focus for advancements in treatment planning for radiation therapy. As these are starting to become incorporated into the clinical workflow, a major concern from clinic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53b6cc02cc658cf121623a1b15fa6936
https://pubmed.ncbi.nlm.nih.gov/33503599
https://pubmed.ncbi.nlm.nih.gov/33503599
Publikováno v:
Med Phys
We propose to develop deep learning models that can predict Pareto optimal dose distributions by using any given set of beam angles, along with patient anatomy, as input to train the deep neural networks. We implement and compare two deep learning ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::802e186a88bcd6459e8bb409dbba7c55
Autor:
Yesenia Gonzalez, Dan Nguyen, Azar Sadeghnejad Barkousaraie, Raquibul Hannan, Neil Desai, Steve B. Jiang, Anjali Balagopal, Yaochung Weng, Michael Dohopolski, Aurelie Garant, Mu-Han Lin, Howard E. Morgan
In post-operative radiotherapy for prostate cancer, precisely contouring the clinical target volume (CTV) to be irradiated is challenging, because the cancerous prostate gland has been surgically removed, so the CTV encompasses the microscopic spread
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c06aa7e658470f49bcabae96e52da627
Publikováno v:
Journal of the Operational Research Society. 68:14-33
We study the convoy movement problem in peacetime from a civilian perspective by seeking to minimize civilian traffic disruptions. We develop an exact hybrid algorithm that combines the k-shortest path algorithm along with finding a minimum weighted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70ca6fa7e997df62b34696645fd0f18f
https://doi.org/10.1057/s41274-016-0001-x
https://doi.org/10.1057/s41274-016-0001-x
Autor:
Azar Sadeghnejad Barkousaraie, Chenyang Shen, Rafe McBeth, Gyanendra Bohara, Xun Jia, Steve B. Jiang, Dan Nguyen
Publikováno v:
Med Phys
PURPOSE: We propose a novel domain specific loss, which is a differentiable loss function based on the dose volume histogram, and combine it with an adversarial loss for the training of deep neural networks. In this study, we trained a neural network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fab5bfc305c819b8412c11049aab2a5d
https://pubmed.ncbi.nlm.nih.gov/31821577
https://pubmed.ncbi.nlm.nih.gov/31821577
Publikováno v:
Med Phys
PURPOSE: Beam orientation selection, whether manual or protocol-based, is the current clinical standard in radiation therapy treatment planning, but it is tedious and can yield suboptimal results. Many algorithms have been designed to optimize beam o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aacaf660f2d53bfb6f45cfe43715304a
https://pubmed.ncbi.nlm.nih.gov/31868927
https://pubmed.ncbi.nlm.nih.gov/31868927
Publikováno v:
Artificial Intelligence in Radiation Therapy ISBN: 9783030324858
AIRT@MICCAI
AIRT@MICCAI
In clinical practice, the beam orientation selection process is either tediously done by the planner or based on specific protocols, typically yielding suboptimal and inefficient solutions. Column generation (CG) has been shown to produce superior pl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3fbe04739a642f0fb59e9994a87e7a2
https://doi.org/10.1007/978-3-030-32486-5_1
https://doi.org/10.1007/978-3-030-32486-5_1
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 53:733-750
In this paper, we present a combination of particle swarm optimization (PSO) and genetic operators for a multi-objective job shop scheduling problem that minimizes the mean weighted completion time and the sum of the weighted tardiness/earliness cost
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6491e9a6557cee0699b69a7d4c9573b
https://doi.org/10.1007/s00170-010-2847-4
https://doi.org/10.1007/s00170-010-2847-4