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Table 3 Literature review for oncologic imaging or phantom studies with magnetic resonance imaging

From: Radiomics in medical imaging—“how-to” guide and critical reflection

  Ref. Study (first author) Year Factor Site/Organ
Test-retest [102] Bianchini et al. 2020   Phantom
[9] Baessler et al. 2019   Phantom
[103] Fiset et al. 2019   Cervical cancer
[35] Mahon et al. 2019   NSCLC
[104] Peerlings et al. 2019   Ovarian cancer, lung cancer, colorectal liver metastasis
[105] Schwier et al. 2019   Prostate
Acquisition [9] Baessler et al. 2019 Matrix size Phantom
[106] Bologna et al. 2019 TR, TE, INU, noise level Phantom
[107] Cattell et al. 2019 Noise level Phantom
[103] Fiset et al. 2019 Scanner Cervical cancer
[108] Um et al. 2019 Scanner, field strength Glioblastoma
[109] Yang et al. 2018 Noise level, accelerator factor Phantom, glioma
Reconstruction [9] Baessler et al. 2019 Matrix size Phantom
[106] Bologna et al. 2019 Voxel size Phantom
[107] Cattell et al. 2019 Voxel size Phantom
[109] Yang et al. 2018 Algorithm Phantom, glioma
Segmentation [110] Traverso et al. 2020   Cervical cancer
[9] Baessler et al. 2019   Phantom
[107] Cattell et al. 2019   Phantom
[111] Duron et al. 2019   Lacrymal gland tumors, breast lesions
[103] Fiset et al. 2019   Cervical cancer
[112] Tixier et al. 2019   Glioblastoma
[113] Zhang et al. 2019   Nasopharyngeal carcinoma, sentinel lymph node
[114] Saha et al. 2018   Breast cancer
[115] Veeraraghavan et al. 2018   Breast cancer
Image processing [116] Isaksson et al. 2020 Normalization Prostate cancer
[117] Scalco et al. 2020 Normalization Prostate cancer
[110] Traverso et al. 2020 Normalization, discretization, filtering Cervical cancer
[106] Bologna et al. 2019 Normalization, resampling, filtering Phantom
[111] Duron et al. 2019 Discretization Lacrymal gland tumors, breast lesions
[118] Moradmand et al. 2019 Bias field correction, filtering Glioblastoma
[119] Um et al. 2019 Bias field correction, normalization, discretization, filtering Glioblastoma