Publications of Nadieh Khalili

all all years 2025 2024 2023 2019

Papers in international journals

  1. N. Khalili and F. Ciompi, "Scaling data toward pan-cancer foundation models", Trends in Cancer, 2024;10:871-872.
    DOI PMID
  2. F. Khoraminia, F. de Jong, F. Akram, G. Litjens, M. Jansen, A. Gonzalez, D. Lichtenburg, A. Stubbs, N. Khalili and T. Zuiverloon, "Abstract B004: Deep learning unveils molecular footprints in histology: predicting molecular subtypes from bladder cancer histology slides", Clinical Cancer Research, 2024;30:B004-B004.
    Abstract DOI
  3. R. Zoetmulder, L. Baak, N. Khalili, H. Marquering, N. Wagenaar, M. Benders, N. van der Aa and I. Isgum, "Brain segmentation in patients with perinatal arterial ischemic stroke", NeuroImage: Clinical, 2023;38:103381.
    DOI PMID Cited by ~1
  4. N. Khalili, N. Lessmann, E. Turk, N. Claessens, R. de Heus, T. Kolk, M. Viergever, M. Benders and I. Išgum, "Automatic brain tissue segmentation in fetal MRI using convolutional neural networks", Magnetic Resonance Imaging, 2019;64:77-89.
    DOI PMID Cited by ~91

Preprints

  1. N. Khalili, J. Spronck, F. Ciompi, J. van der Laak and G. Litjens, "Uncertainty-guided annotation enhances segmentation with the human-in-the-loop", arXiv:2404.07208, 2024.
    Abstract DOI arXiv
  2. D. Schouten, G. Nicoletti, B. Dille, C. Chia, P. Vendittelli, M. Schuurmans, G. Litjens and N. Khalili, "Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications", arXiv:2411.03782, 2024.
    Abstract DOI arXiv

Papers in conference proceedings

  1. C. Lems, N. Klubíčková, B. Brattoli, T. Lee, S. Kim, V. Besler, P. Fernandez, L. Pons, A. Laurinavicius, J. Drachneris, D. Montezuma, D. Oliveira, S. Vos, M. Balkenhol, J. van Ipenburg, A. Vos, M. Poceviciute, N. Khalili and F. Ciompi, "Towards a multicentric open DigitAL PatHology assIstant beNchmark: Initial Results from the DALPHIN Study", Laboratory Investigation, 2025;105:103609.
    DOI
  2. N. Khalili, J. Spronck, F. Ciompi, J. der Van Laak and G. Litjens, "A human-in-the-loop framework for refining deep learning models in pathology segmentation", Medical Imaging 2025: Digital and Computational Pathology, 2025:21.
    DOI

Abstracts

  1. D. Schouten, N. Khalili, J. van der Laak and G. Litjens, "Full Resolution Three-Dimensional Reconstruction of Non-Serial Prostate Whole-Mounts: Pilot Validation and Initial Results", European Congress on Digital Pathology, 2024.
    Abstract
  2. N. Khalili, N. Lessmann, E. Turk, M. Viergever, M. Benders and I. Isgum, "Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2019.