Publications of Ecem Sogancioglu

all all years 2022 2021 2020 2019 2018

Papers in international journals

  1. E. Calli, B. Van Ginneken, E. Sogancioglu and K. Murphy, "FRODO: An in-depth analysis of a system to reject outlier samples from a trained neural network.", IEEE transactions on medical imaging, 2022;PP.
    Abstract DOI PMID
  2. E. Sogancioglu, K. Murphy, E. Th Scholten, L. Boulogne, M. Prokop and B. van Ginneken, "Automated estimation of total lung volume using chest radiographs and deep learning", Medical Physics, 2022;49(7):4466-4477.
    Abstract DOI PMID
  3. J. Noothout, N. Lessmann, M. Eede, L. van Harten, E. Sogancioglu, F. Heslinga, M. Veta, B. van Ginneken and I. Isgum, "Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation", Journal of Medical Imaging, 2022.
    Abstract DOI
  4. E. Calli, E. Sogancioglu, B. van Ginneken, K. van Leeuwen and K. Murphy, "Deep learning for chest X-ray analysis: A survey", Medical Image Analysis, 2021;72:102125.
    Abstract DOI PMID Download
  5. E. Sogancioglu, K. Murphy, E. Calli, E. Scholten, S. Schalekamp and B. Van Ginneken, "Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification", IEEE Access, 2020;8:94631-94642.
    Abstract DOI

Preprints

  1. D. Belli, S. Hu, E. Sogancioglu and B. van Ginneken, "Chest X-Rays Image Inpainting with Context Encoders", arXiv:1812.00964, 2018.
    Abstract arXiv
  2. E. Sogancioglu, S. Hu, D. Belli and B. van Ginneken, "Chest X-ray Inpainting with Deep Generative Models", arXiv:1809.01471, 2018.
    Abstract arXiv Cited by ~4

Papers in conference proceedings

  1. E. Calli, E. Sogancioglu, E. Scholten, K. Murphy and B. van Ginneken, "Handling label noise through model confidence and uncertainty: application to chest radiograph classification", Medical Imaging, 2019(1).
    Abstract DOI Cited by ~4
  2. E. Calli, K. Murphy, E. Sogancioglu and B. van Ginneken, "FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis", Medical Imaging with Deep Learning, 2019.
    Abstract Url Cited by ~4