Výsledky vyhledávání - "Melina Hosseiny"

Akademický článek

Exploring Uncertainty Measures in Bayesian Deep Attentive Neural Networks for Prostate Zonal Segmentation

Autor: Yongkai Liu, Guang Yang, Melina Hosseiny, Afshin Azadikhah, Sohrab Afshari Mirak, Qi Miao, Steven S. Raman, Kyunghyun Sung

Publikováno v: IEEE Access, Vol 8, Pp 151817-151828 (2020)

Automatic segmentation of prostatic zones on multi-parametric MRI (mpMRI) can improve the diagnostic workflow of prostate cancer. We designed a spatial attentive Bayesian deep learning network for the automatic segmentation of the peripheral zone (PZ

Externí odkaz: https://doaj.org/article/4a6487d82e084725b40029a62f56e93d

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Akademický článek

Automatic Prostate Zonal Segmentation Using Fully Convolutional Network With Feature Pyramid Attention

Autor: Yongkai Liu, Guang Yang, Sohrab Afshari Mirak, Melina Hosseiny, Afshin Azadikhah, Xinran Zhong, Robert E. Reiter, Yeejin Lee, Steven S. Raman, Kyunghyun Sung

Publikováno v: IEEE Access, Vol 7, Pp 163626-163632 (2019)

Our main objective in the paper is to develop a novel deep learning-based algorithm for automatic segmentation of prostate zones and to evaluate the performance of the algorithm on an additional independent testing dataset in comparison with inter-re

Externí odkaz: https://doaj.org/article/5646b8eb73dc45f6b8bad1645594afd3

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Akademický článek

Differentiation between benign and malignant thyroid nodules using diffusion-weighted imaging, a 3-T MRI study

Autor: Leila Aghaghazvini, Hashem Sharifian, Nasrin Yazdani, Melina Hosseiny, Saina Kooraki, Pirouz Pirouzi, Afsoon Ghadiri, Madjid Shakiba, Soheil Kooraki

Publikováno v: Indian Journal of Radiology and Imaging, Vol 28, Iss 04, Pp 460-464 (2018)

Background: Preoperative differentiation of benign from malignant thyroid nodules remains a challenge. Aims: This study assessed the accuracy of diffusion-weighted imaging (DWI) for differentiation between benign and malignant thyroid nodules. Materi

Externí odkaz: https://doaj.org/article/6a3ac5567b3141e38a9cb4445ea87e67

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Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer

Autor: Haoxin Zheng, Qi Miao, Yongkai Liu, Sohrab Afshari Mirak, Melina Hosseiny, Fabien Scalzo, Steven S. Raman, Kyunghyun Sung

Publikováno v: Eur Radiol

To identify which patient with prostate cancer (PCa) could safely avoid extended pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a radiomics-based machine learning approach.An integrative radiomics model (IRM) was pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d65ce843397c2db4c55b5c5a76961043
https://doi.org/10.1007/s00330-022-08625-6

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COVID-19 pandemic revisited: lessons the radiology community has learned a year later

Autor: Robert C. Gilkeson, Ali Gholamrezanezhad, Amit Gupta, Erik Velez, Melina Hosseiny, Steven S. Raman, Soheil Kooraki

Publikováno v: Emergency Radiology

For more than 1 year, COVID-19 pandemic has impacted every aspect of our lives. This paper reviews the major challenges that the radiology community faced over the past year and the impact the pandemic had on the radiology practice, radiologist-in-tr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e40f97e77ad85530c09a65b306e4831d
https://doi.org/10.1007/s10140-021-01985-4

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Read-out Segmented Echo Planar Imaging with Two-Dimensional Navigator Correction (RESOLVE): An Alternative Sequence to Improve Image Quality on Diffusion-Weighted Imaging of Prostate

Autor: Melina Hosseiny, Kyung Hyun Sung, Ely Felker, Voraparee Suvannarerg, Teeravut Tubtawee, Ariel Shafa, Krishan R. Arora, Justin Ching, Anjalie Gulati, Afshin Azadikhah, Xiaodong Zhong, James Sayre, David Lu, Steven S Raman

Publikováno v: The British journal of radiology. 95(1136)

Objective: We aimed to investigate if the use of read-out segmented echoplanar imaging with additional two-dimensional navigator correction (Readout Segmentation of Long Variable Echo, RESOLVE) for acquiring prostate diffusion-weighted imaging (DWI)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fc982a3008a3b710b34f5ca5f1d0442
https://pubmed.ncbi.nlm.nih.gov/35671135

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Efficacy of 3T Multiparametric MR Imaging followed by 3T in-Bore MR-Guided Biopsy for Detection of Clinically Significant Prostate Cancer Based on PIRADSv2.1 Score

Autor: Ely Felker, Preeti Ahuja, Melina Hosseiny, Afshin Azadikhah, David S.K. Lu, Steven S. Raman, Danielle Ponzini, James Sayre, Voraparee Suvannarerg

Publikováno v: Journal of Vascular and Interventional Radiology. 31:1619-1626

Purpose To evaluate the diagnostic yield of 3T in-bore magnetic resonance-guided biopsy (3T IB-MRGB) for detection of clinically significant prostate cancer (csPCa), based on assessment using the Prostate Imaging Reporting and Data System version 2.1

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::347cf1b60329e508f8a37da5ca2643ed
https://doi.org/10.1016/j.jvir.2020.03.002

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