Ciompi, Francesco

A survey on deep learning in medical image analysis

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 15,332

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

Setio, A. A. A., Ciompi, F., Litjens, G., Gerke, P., Jacobs, C., van Riel, S. J., Wille, M. M. W., Naqibullah, M., Sanchez, C. I., & van Ginneken, B. (2016) · IEEE Transactions on Medical Imaging

AI in cancer detectionLung Cancer Diagnosis and Treatment

Cited by 1,258

Deep learning in histopathology: the path to the clinic

van der Laak, J., Litjens, G., & Ciompi, F. (2021) · Nature Medicine

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 902

Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology

Tellez, D., Litjens, G., Bándi, P., Bulten, W., Bokhorst, J.-M., Ciompi, F., & van der Laak, J. (2019) · Medical Image Analysis

AI in cancer detectionDigital Imaging for Blood Diseases

Cited by 649

Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box

Ciompi, F., de Hoop, B., van Riel, S. J., Chung, K., Scholten, E. T., Oudkerk, M., de Jong, P. A., Prokop, M., & Ginneken, B. V. (2015) · Medical Image Analysis

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 289

Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Tellez, D., Balkenhol, M., Otte-Höller, I., van de Loo, R., Vogels, R., Bult, P., Wauters, C., Vreuls, W., Mol, S., Karssemeijer, N., et al. (2018) · IEEE Transactions on Medical Imaging

AI in cancer detectionCell Image Analysis Techniques

Cited by 288

Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans

van Ginneken, B., Setio, A. A. A., Jacobs, C., & Ciompi, F. (2015) · 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 278

Generating dermatopathology reports from gigapixel whole slide images with HistoGPT

Tran, M., Schmidle, P., Guo, R. R., Wagner, S. J., Koch, V., Lupperger, V., Novotny, B., Murphree, D. H., Hardway, H. D., D’Amato, M., et al. (2025) · Nature Communications

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 36

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

van Eekelen, L., Spronck, J., Looijen-Salamon, M., Vos, S., Munari, E., Girolami, I., Eccher, A., Acs, B., Boyaci, C., de Souza, G. S., et al. (2024) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 21

HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

van Rijthoven, M., Balkenhol, M., Siliņa, K., van der Laak, J., & Ciompi, F. (2021) · Medical Image Analysis

AI in cancer detectionMedical Image Segmentation Techniques

Cited by 16

Uncertainty-guided annotation enhances segmentation with the human-in-the-loop

Khalili, N., Spronck, J., Ciompi, F., van der Laak, J., & Litjens, G. (2024) · arXiv

AI in cancer detectionMedical Image Segmentation Techniques

Cited by 1