Publications of Nadieh Khalili

all all years 2024 2023 2019

2024

Papers in international journals

  1. N. Khalili and F. Ciompi, "Scaling data toward pan-cancer foundation models", Trends in Cancer, 2024;10:871-872.
    Abstract 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

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

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

2023

Papers in international journals

  1. 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.
    Abstract DOI PMID Cited by ~1

2019

Papers in international journals

  1. 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.
    Abstract DOI PMID Cited by ~91

Abstracts

  1. 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.
    Abstract