Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Naciye S, Gezer"'
Autor:
Cameron Beeche, Jatin P Singh, Joseph K Leader, Naciye S Gezer, Amechi P Oruwari, Kunal K Dansingani, Jay Chhablani, Jiantao Pu
Publikováno v:
Pattern recognition. 128
To develop and validate a novel convolutional neural network (CNN) termed "Super U-Net" for medical image segmentation.Super U-Net integrates a dynamic receptive field module and a fusion upsampling module into the classical U-Net architecture. The m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::538d6bc9128f49ce7bad74eedb48767d
https://pubmed.ncbi.nlm.nih.gov/35528144
https://pubmed.ncbi.nlm.nih.gov/35528144
Autor:
Kartik Iyer, Cameron A. Beeche, Naciye S. Gezer, Joseph K. Leader, Shangsi Ren, Rajeev Dhupar, Jiantao Pu
Publikováno v:
Journal of Clinical Medicine; Volume 12; Issue 6; Pages: 2106
Background: Body composition can be accurately quantified based on computed tomography (CT) and typically reflects an individual’s overall health status. However, there is a dearth of research examining the relationship between body composition and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::563ba54f12f1f847f7295c582d859483
Autor:
Lucy, Pu, Syed F, Ashraf, Naciye S, Gezer, Iclal, Ocak, Daniel E, Dresser, Joseph K, Leader, Rajeev, Dhupar
Background Estimating whole-body composition from limited region-computed tomography (CT) scans has many potential applications in clinical medicine; however, it is challenging. Purpose To investigate if whole-body composition based on several tissue
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9e400ca237c365de8dbdb9955c4d96c
https://avesis.deu.edu.tr/publication/details/1465831d-e42c-4d0a-beec-c8aebe689cf5/oai
https://avesis.deu.edu.tr/publication/details/1465831d-e42c-4d0a-beec-c8aebe689cf5/oai
Autor:
Cameron Beeche, Naciye S Gezer, Kartik Iyer, Omar Almetwali, Juezhao Yu, Yanchun Zhang, Rajeev Dhupar, Joseph K. Leader, Jiantao Pu
Objective To develop and validate a novel deep learning architecture to classify retinal vein occlusion (RVO) on color fundus photographs (CFPs) and reveal the image features contributing to the classification. Methods The neural understanding networ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa2f5d4e50eabac2f520c0ccdc6483c3
https://avesis.deu.edu.tr/publication/details/d8c613e7-f1ff-4afd-9349-e549e1371c91/oai
https://avesis.deu.edu.tr/publication/details/d8c613e7-f1ff-4afd-9349-e549e1371c91/oai
Autor:
Naciye S. Gezer, Andriy I. Bandos, Cameron A. Beeche, Joseph K. Leader, Rajeev Dhupar, Jiantao Pu
Publikováno v:
Lung Cancer. 179:107189
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40aa338f8a95325f08cfb44aa29d07b8
https://doi.org/10.1016/j.lungcan.2023.107189
https://doi.org/10.1016/j.lungcan.2023.107189