Deprest, Jan

Interactive medical image segmentation using deep learning with image-specific fine tuning

Wang, G., Li, W., Zuluaga, M. A., Pratt, R., Patel, P. A., Aertsen, M., Doel, T., David, A. L., Deprest, J., Ourselin, S., et al. (2018) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 843

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

Wang, G., Li, W., Aertsen, M., Deprest, J., Ourselin, S., & Vercauteren, T. (2019) · Neurocomputing

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 659

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

Wang, G., Zuluaga, M. A., Li, W., Pratt, R., Patel, P. A., Aertsen, M., Doel, T., David, A. L., Deprest, J., Ourselin, S., et al. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 502

An international urogynecological association (IUGA)/international continence society (ICS) joint terminology and classification of the complications related directly to the insertion of prostheses (meshes, implants, tapes) and grafts in female pelvic floor surgery

Haylen, B. T., Freeman, R. M., Swift, S. E., Cosson, M., Davila, G. W., Deprest, J., Dwyer, P. L., Fatton, B., Kocjancic, E., Lee, J., et al. (2011) · Neurourology and Urodynamics

Pelvic floor disorders treatmentsHernia repair and management

Cited by 443

ToolNet: Holistically-nested real-time segmentation of robotic surgical tools

Garcia-Peraza-Herrera, L. C., Li, W., Fidon, L., Gruijthuijsen, C., Devreker, A., Attilakos, G., Deprest, J., Poorten, E. V., Stoyanov, D., Vercauteren, T., et al. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 137

MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning

Luo, X., Wang, G., Song, T., Zhang, J., Aertsen, M., Deprest, J., Ourselin, S., Vercauteren, T., & Zhang, S. (2021) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 126

The effect of the first vaginal birth on pelvic floor anatomy and dysfunction

Urbankova, I., Grohregin, K., Hanacek, J., Krcmar, M., Feyereisl, J., Deprest, J., & Krofta, L. (2019) · International Urogynecology Journal

Pelvic floor disorders treatmentsPregnancy-related medical research

Cited by 99

Pregnancy, labour and delivery as risk factors for pelvic organ prolapse: a systematic review

Cattani, L., Decoene, J., Page, A.-S., Weeg, N., Deprest, J., & Dietz, H. P. (2021) · International Urogynecology Journal

Pelvic floor disorders treatmentsPregnancy-related medical research

Cited by 94

Assessment of lung area in fetuses with congenital diaphragmatic hernia

Jani, J., Peralta, C. F. A., Benachi, A., Deprest, J., & Nicolaides, K. H. (2007) · Ultrasound in Obstetrics & Gynecology

Congenital Diaphragmatic Hernia StudiesCongenital Anomalies and Fetal Surgery

Cited by 76

Slic-Seg: A minimally interactive segmentation of the placenta from sparse and motion-corrupted fetal MRI in multiple views

Wang, G., Zuluaga, M. A., Pratt, R., Aertsen, M., Doel, T., Klusmann, M., David, A. L., Deprest, J., Vercauteren, T., & Ourselin, S. (2016) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 73

Graft‐related complications and biaxial tensiometry following experimental vaginal implantation of flat mesh of variable dimensions

Manodoro, S., Endo, M., Uvin, P., Albersen, M., Vláčil, J., Engels, A., Schmidt, B., De Ridder, D., Feola, A., & Deprest, J. (2013) · BJOG: An International Journal of Obstetrics & Gynaecology

Hernia repair and managementPelvic floor disorders treatments

Cited by 65

Hysteropexy in the treatment of uterine prolapse stage 2 or higher: laparoscopic sacrohysteropexy versus sacrospinous hysteropexy. A multicentre randomised controlled trial (LAVA trial)

van IJsselmuiden, M., van Oudheusden, A., Veen, J., van de Pol, G., Vollebregt, A., Radder, C., Housmans, S., van Kuijk, S., Deprest, J., Bongers, M., et al. (2020) · BJOG: An International Journal of Obstetrics & Gynaecology

Pelvic floor disorders treatmentsUterine Myomas and Treatments

Cited by 47

Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings

Williams, H., Cattani, L., Van Schoubroeck, D., Yaqub, M., Sudre, C., Vercauteren, T., D'Hooge, J., & Deprest, J. (2021) · Ultrasound in Medicine & Biology

Medical Image Segmentation TechniquesPelvic floor disorders treatments

Cited by 19

Immunological Ignorance Allows Long-Term Gene Expression After Perinatal Recombinant Adeno-Associated Virus-Mediated Gene Transfer to Murine Airways

Carlon, M. S., Vidović, D., Dooley, J., da Cunha, M. M., Maris, M., Lampi, Y., Toelen, J., Van den Haute, C., Baekelandt, V., Deprest, J., et al. (2014) · Human Gene Therapy

Virus-based gene therapy researchRNA Interference and Gene Delivery

Cited by 19

Dynamically Balanced Online Random Forests for Interactive Scribble-Based Segmentation

Wang, G., Zuluaga, M. A., Pratt, R., Aertsen, M., Doel, T., Klusmann, M., David, A. L., Deprest, J., Vercauteren, T., & Ourselin, S. (2016) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesImbalanced Data Classification Techniques

Cited by 14

Correction: The proportion of alveolar type 1 cells decreases in murine hypoplastic congenital diaphragmatic hernia lungs

Nguyen, T. M., Jimenez, J., Rendin, L. E., Müller, C., Westergren-Thorsson, G., Deprest, J., & Toelen, J. (2019) · PLOS ONE

Congenital Diaphragmatic Hernia StudiesNeonatal Respiratory Health Research

Cited by 2