Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability
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Texture analysis of medical images for radiotherapy applications.A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.Accounting for reconstruction kernel-induced variability in CT radiomic features using noise power spectra.
P2860
Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Impact of Reconstruction Algor ...... truction Algorithm Variability
@ast
Impact of Reconstruction Algor ...... truction Algorithm Variability
@en
type
label
Impact of Reconstruction Algor ...... truction Algorithm Variability
@ast
Impact of Reconstruction Algor ...... truction Algorithm Variability
@en
prefLabel
Impact of Reconstruction Algor ...... truction Algorithm Variability
@ast
Impact of Reconstruction Algor ...... truction Algorithm Variability
@en
P2093
P2860
P1433
P1476
Impact of Reconstruction Algor ...... truction Algorithm Variability
@en
P2093
Chang Min Park
Eui Jin Hwang
Hyungjin Kim
Jong Hyuk Lee
Myunghee Lee
Sang Joon Park
Yong Sub Song
P2860
P304
P356
10.1371/JOURNAL.PONE.0164924
P407
P50
P577
2016-10-14T00:00:00Z