Research map: Reproducibility and discriminative power of MRI liver radiomics: Impact of deep learning-based image reconstruction

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  1. 3D Slicer as an image computing platform for the Quantitative Imaging Network · Andriy Fedorov · 2012 · 9319 citations · Cited by this paper
  2. Refined risk stratification with O-RADS ultrasound v2022: Diagnostic performance compared with v2019 and the ADNEX model · 2026 · Related
  3. Radiomics: Extracting more information from medical images using advanced feature analysis · Philippe Lambin · 2012 · 6221 citations · Cited by this paper
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  5. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach · Hugo J.W.L. Aerts · 2014 · 5293 citations · Cited by this paper
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  7. The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping · Alex Zwanenburg · 2020 · 4183 citations · Cited by this paper
  8. First-in-human pilot study of a robotic-assisted system for image-guided trans-thoracic lung biopsy: Clinical feasibility and exploratory post-hoc AI trajectory analysis · 2026 · Related
  9. Shortcut learning in deep neural networks · Robert Geirhos · 2020 · 2142 citations · Cited by this paper
  10. gBOLD-CSF coupling as a noninvasive predictor of cognitive recovery after shunt surgery in Idiopathic normal pressure hydrocephalus · 2026 · Related
  11. CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII · Burak Koçak · 2023 · 466 citations · Cited by this paper
  12. The non-zero-calcification-risk multi-ethnic study of atherosclerosis score correlates with extent of coronary calcification as well as coronary artery disease · 2026 · Related
  13. Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis · Alex Zwanenburg · 2019 · 316 citations · Cited by this paper
  14. Feasibility of early detection of left ventricular diastolic dysfunction in hypertensive patients using four-dimensional flow cardiac magnetic resonance · 2026 · Related
  15. Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial · Jurgen Peerlings · 2019 · 271 citations · Cited by this paper
  16. Comparative diagnostic performance of ultrasound and magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: a head-to-head meta-analysis · 2026 · Related
  17. Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers · Masafumi Kidoh · 2019 · 243 citations · Cited by this paper
  18. RECIST 1.1 and PERCIST for response assessment in metastatic breast cancer: feasibility and agreement in a real‑world retrospective cohort study · 2026 · Related
  19. Robustness and Reproducibility of Radiomics in Magnetic Resonance Imaging · Bettina Baeßler · 2018 · 234 citations · Cited by this paper
  20. An MRI-Based classification of osteonecrosis of the femoral head based on the spatial relationship between the epiphyseal line and osteonecrotic boundary · 2026 · Related
  21. Disentangled representation learning in cardiac image analysis · Agisilaos Chartsias · 2019 · 202 citations · Cited by this paper
  22. Gray-level discretization impacts reproducible MRI radiomics texture features · Loïc Duron · 2019 · 190 citations · Cited by this paper
  23. Clinical Impact of Deep Learning Reconstruction in MRI · Shigeru Kiryu · 2023 · 156 citations · Cited by this paper
  24. Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study · Rafael Ortiz-Ramón · 2018 · 145 citations · Cited by this paper
  25. A decade of radiomics research: are images really data or just patterns in the noise? · Daniel Pinto dos Santos · 2020 · 134 citations · Cited by this paper
  26. Early Readout on Overall Survival of Patients With Melanoma Treated With Immunotherapy Using a Novel Imaging Analysis · Laurent Dercle · 2022 · 99 citations · Cited by this paper
  27. Harmonization Strategies in Multicenter MRI-Based Radiomics · Elisavet Stamoulou · 2022 · 73 citations · Cited by this paper
  28. Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing · Alberto Traverso · 2019 · 68 citations · Cited by this paper
  29. Short-term reproducibility of radiomic features in liver parenchyma and liver malignancies on contrast-enhanced CT imaging · Thomas Perrin · 2018 · 56 citations · Cited by this paper
  30. Influence of Image Processing on Radiomic Features From Magnetic Resonance Imaging · Barbara Daria Wichtmann · 2022 · 56 citations · Cited by this paper
  31. ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics · João Santinha · 2024 · 49 citations · Cited by this paper
  32. Robustness of radiomics to variations in segmentation methods in multimodal brain MRI · Maarten G. Poirot · 2022 · 45 citations · Cited by this paper
  33. Intra- and inter-operator variability in MRI-based manual segmentation of HCC lesions and its impact on dosimetry · Elise C. Covert · 2022 · 41 citations · Cited by this paper
  34. Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study · Jingyu Zhong · 2022 · 40 citations · Cited by this paper
  35. Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging: a phantom study · Florian Michallek · 2022 · 36 citations · Cited by this paper
  36. Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique · Masahiro Tanabe · 2021 · 34 citations · Cited by this paper
  37. Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes · Martha Foltyn‐Dumitru · 2023 · 33 citations · Cited by this paper
  38. A multicenter study on radiomic features from T 2 ‐weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics · Linda Bianchini · 2020 · 28 citations · Cited by this paper
  39. Impact of Deep Learning Reconstruction Combined With a Sharpening Filter on Single-Shot Fast Spin-Echo T2-Weighted Magnetic Resonance Imaging of the Uterus · Takahiro Tsuboyama · 2022 · 27 citations · Cited by this paper

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