Zaigham Saghir

Zaigham Saghir

Clinical Associate Professor

Member of:

  • Internal Medicine: Respiratory Medicine


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  1. Published

    'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial

    Røe, O. D., Markaki, M., Tsamardinos, I., Lagani, V., Nguyen, O. T. D., Pedersen, J. H., Saghir, Zaigham & Ashraf, H. G., 2019, In: BMJ Open Respiratory Research. 6, 1, 9 p., e000512.

    Research output: Contribution to journal › Journal article › Research › peer-review

  2. Published

    A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs

    Juarez, A. G., Selvan, Raghav, Saghir, Zaigham & de Bruijne, Marleen, 22 Aug 2019, Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Springer, p. 583-591 (Lecture Notes in Computer Science, Vol. LNCS 11861).

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  3. Published

    Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks

    Garcia-uceda, A., Selvan, Raghav, Saghir, Zaigham, Tiddens, H. A. W. M. & de Bruijne, Marleen, 2021, In: Scientific Reports. 11, 1, 15 p., 16001.

    Research output: Contribution to journal › Journal article › Research › peer-review

  4. Published

    Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem

    Tennakoon, R., Bortsova, G., Orting, S., Gostar, A. K., Wille, M. M. W., Saghir, Zaigham, Hoseinnezhad, R., de Bruijne, Marleen & Bab-Hadiashar, A., 2020, In: IEEE Transactions on Medical Imaging. 39, 4, p. 854-865

    Research output: Contribution to journal › Journal article › Research › peer-review

  5. Published

    Creating a training set for artificial intelligence from initial segmentations of airways

    Dudurych, I., Garcia-Uceda, A., Saghir, Zaigham, Tiddens, H. A. W. M., Vliegenthart, R. & de Bruijne, Marleen, 2021, In: European radiology experimental. 5, 1, 7 p., 54.

    Research output: Contribution to journal › Journal article › Research › peer-review

  6. Published

    Deep learning for malignancy risk estimation of pulmonary nodules detected at low-dose screening CT

    Venkadesh, K. V., Setio, A. A. A., Schreuder, A., Scholten, E. T., Chung, K., Wille, M. M. W., Saghir, Zaigham, van Ginneken, B., Prokop, M. & Jacobs, C., 2021, In: Radiology. 300, 2, p. 438-447 10 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  7. Accepted/In press

    Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation

    Peeters, D., Alves, N., Venkadesh, K. V., Dinnessen, R., Saghir, Zaigham, Scholten, E. T., Schaefer-Prokop, C., Vliegenthart, R., Prokop, M. & Jacobs, C., 2024, (Accepted/In press) In: European Radiology.

    Research output: Contribution to journal › Journal article › Research › peer-review

  8. Published

    Growth of the thoracic aorta in the smoking population: The Danish Lung Cancer Screening Trial

    Bons, L. R., Sedghi Gamechi, Z., Thijssen, C. G. E., Kofoed, Klaus Fuglsang, Pedersen, J. H., Saghir, Zaigham, Takkenberg, J. J. M., Kardys, I., Budde, R. P. J., de Bruijne, Marleen & Roos-Hesselink, J. W., 2020, In: International Journal of Cardiology. 299, p. 276-281

    Research output: Contribution to journal › Journal article › Research › peer-review

  9. Published

    Increased respiratory morbidity in individuals with interstitial lung abnormalities

    Hoyer, N., Thomsen, L. H., Wille, M. M. W., Wilcke, T., Dirksen, A., Pedersen, J. H., Saghir, Zaigham, Ashraf, H. & Shaker, Saher Burhan, 19 Mar 2020, In: BMC Pulmonary Medicine. 20, 1, 10 p., 67.

    Research output: Contribution to journal › Journal article › Research › peer-review

  10. Published

    Intrapleural fibrinolysis and DNase versus video-assisted thoracic surgery (VATS) for the treatment of pleural empyema (FIVERVATS): Protocol for a randomised, controlled trial - Surgery as first-line treatment

    Christensen, T. D., Bendixen, M., Skaarup, S. H., Jensen , Jens-Ulrik Stæhr , Petersen, René Horsleben, Christensen, M., Licht, P., Neckelmann, K., Bibby, B. M., Møller, L. B., Bodtger, U., Borg, M. H., Saghir, Zaigham, Langfeldt, S., Harders, S. M. W., Bedawi, E. O., Naidu, B., Rahman, N. & Laursen, C. B., 2022, In: BMJ Open. 12, 3, e054236.

    Research output: Contribution to journal › Journal article › Research › peer-review

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