Skip to main content

Advanced Image Analysis (Artificial Intelligence, Radiomics)

  1. To investigate the value of 18F-FDG PET/CT molecular radiomics combined with a clinical model in predicting thoracic lymph node metastasis (LNM) in invasive lung adenocarcinoma (≤ 3 cm).

    Authors: Cheng Chang, Maomei Ruan, Bei Lei, Hong Yu, Wenlu Zhao, Yaqiong Ge, Shaofeng Duan, Wenjing Teng, Qianfu Wu, Xiaohua Qian, Lihua Wang, Hui Yan, Ciyi Liu, Liu Liu, Jian Feng and Wenhui Xie
    Citation: EJNMMI Research 2022 12:23
  2. Radiomics is a promising tool for identifying imaging-based biomarkers. Radiomics-based models are often trained on single-institution datasets; however, multi-centre imaging datasets are preferred for externa...

    Authors: Carol Oliveira, Florian Amstutz, Diem Vuong, Marta Bogowicz, Martin Hüllner, Robert Foerster, Lucas Basler, Christina Schröder, Eric I. Eboulet, Miklos Pless, Sandra Thierstein, Solange Peters, Sven Hillinger, Stephanie Tanadini-Lang and Matthias Guckenberger
    Citation: EJNMMI Research 2021 11:79
  3. The prostate-specific membrane antigen (PSMA) is a relevant target in prostate cancer, and immunohistochemistry studies showed associations with outcome. PSMA-ligand positron emission tomography (PET) is incre...

    Authors: Hui Wang, Thomas Amiel, Christoph Würnschimmel, Thomas Langbein, Katja Steiger, Isabel Rauscher, Thomas Horn, Tobias Maurer, Wolfgang Weber, Hans-Juergen Wester, Karina Knorr and Matthias Eiber
    Citation: EJNMMI Research 2021 11:76
  4. To improve the diagnostic accuracy of axillary lymph node (LN) metastasis in breast cancer patients using 2-[18F]FDG-PET/CT, we constructed an artificial intelligence (AI)-assisted diagnosis system that uses deep...

    Authors: Zongyao Li, Kazuhiro Kitajima, Kenji Hirata, Ren Togo, Junki Takenaka, Yasuo Miyoshi, Kohsuke Kudo, Takahiro Ogawa and Miki Haseyama
    Citation: EJNMMI Research 2021 11:10
  5. Careful selection of malignant pleural mesothelioma (MPM) patients for curative treatment is of highest importance, as the multimodal treatment regimen is challenging for patients and harbors a high risk of su...

    Authors: M. Pavic, M. Bogowicz, J. Kraft, D. Vuong, M. Mayinger, S. G. C. Kroeze, M. Friess, T. Frauenfelder, N. Andratschke, M. Huellner, W. Weder, M. Guckenberger, S. Tanadini-Lang and I. Opitz
    Citation: EJNMMI Research 2020 10:81
  6. To establish and validate 18F-fluorodeoxyglucose (18F-FDG) PET/CT-based radiomics model and use it to predict the intermediate-high risk growth patterns in early invasive adenocarcinoma (IAC).

    Authors: Xiaonan Shao, Rong Niu, Xiaoliang Shao, Zhenxing Jiang and Yuetao Wang
    Citation: EJNMMI Research 2020 10:80
  7. The aim of this study was to develop and validate a prognostic model incorporating [18F]FDG PET/CT radiomics for patients of minor salivary gland carcinoma (MSGC).

    Authors: Nai-Ming Cheng, Cheng-En Hsieh, Yu-Hua Dean Fang, Chun-Ta Liao, Shu-Hang Ng, Hung-Ming Wang, Wen-Chi Chou, Chien-Yu Lin and Tzu-Chen Yen
    Citation: EJNMMI Research 2020 10:74
  8. Attenuation correction (AC) of PET data is usually performed using a second imaging for the generation of attenuation maps. In certain situations however—when CT- or MR-derived attenuation maps are corrupted o...

    Authors: Karim Armanious, Tobias Hepp, Thomas Küstner, Helmut Dittmann, Konstantin Nikolaou, Christian La Fougère, Bin Yang and Sergios Gatidis
    Citation: EJNMMI Research 2020 10:53