Advanced Image Analysis (Artificial Intelligence, Radiomics)

In this topical collection (10 articles)

1. Original research

   FDG PET versus CT radiomics to predict outcome in malignant pleural mesothelioma patients

   M. Pavic, M. Bogowicz, J. Kraft, D. Vuong, M. Mayinger, S. G. C. Kroeze… Article:81

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2. Original research

   Value of ¹⁸F-FDG PET/CT-based radiomics model to distinguish the growth patterns of early invasive lung adenocarcinoma manifesting as ground-glass opacity nodules

   **aonan Shao, Rong Niu, **aoliang Shao, Zhenxing Jiang, Yuetao Wang Article:80

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3. Original research

   Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging

   Carol Oliveira, Florian Amstutz, Diem Vuong, Marta Bogowicz… Article:79

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4. Original research

   PSMA-ligand uptake can serve as a novel biomarker in primary prostate cancer to predict outcome after radical prostatectomy

   Hui Wang, Thomas Amiel, Christoph Würnschimmel, Thomas Langbein… Article:76

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5. Original research

   Development and validation of a prognostic model incorporating [¹⁸F]FDG PET/CT radiomics for patients with minor salivary gland carcinoma

   Nai-Ming Cheng, Cheng-En Hsieh, Yu-Hua Dean Fang, Chun-Ta Liao… Article:74

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6. Original research

   Radiomics predictive modeling from dual-time-point FDG PET K_i parametric maps: application to chemotherapy response in lymphoma

   Rezvan Samimi, Isaac Shiri, Yashar Ahmadyar, Jörg van den Hoff… Article:70

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7. Original research

   Independent attenuation correction of whole body [¹⁸F]FDG-PET using a deep learning approach with Generative Adversarial Networks

   Karim Armanious, Tobias Hepp, Thomas Küstner, Helmut Dittmann… Article:53

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8. Original research

   Imaging quality of an artificial intelligence denoising algorithm: validation in ⁶⁸Ga PSMA-11 PET for patients with biochemical recurrence of prostate cancer

   Charles Margail, Charles Merlin, Tommy Billoux, Maxence Wallaert… Article:50

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9. Original research

   Development of a PET/CT molecular radiomics-clinical model to predict thoracic lymph node metastasis of invasive lung adenocarcinoma ≤ 3 cm in diameter

   Cheng Chang, Maomei Ruan, Bei Lei, Hong Yu, Wenlu Zhao, Yaqiong Ge… Article:23

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10. Original research

    Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer

    Zongyao Li, Kazuhiro Kitajima, Kenji Hirata, Ren Togo, Junki Takenaka… Article:10

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