Ledig, Christian

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., et al. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 12,696

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

Kamnitsas, K., Ledig, C., Newcombe, V. F. J., Simpson, J. P., Kane, A. D., Menon, D. K., Rueckert, D., & Glocker, B. (2017) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 3,498

Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research

Maas, A. I. R., Menon, D. K., Adelson, P. D., Andelic, N., Bell, M. J., Belli, A., Bragge, P., Brazinova, A., Büki, A., Chesnut, R. M., et al. (2017) · The Lancet Neurology

Traumatic Brain Injury ResearchTraumatic Brain Injury and Neurovascular Disturbances

Cited by 2,609

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge

Bron, E. E., Smits, M., van der Flier, W. M., Vrenken, H., Barkhof, F., Scheltens, P., Papma, J. M., Steketee, R. M. E., Méndez Orellana, C., Meijboom, R., et al. (2015) · NeuroImage

Dementia and Cognitive Impairment ResearchMedical Image Segmentation Techniques

Cited by 352

DeepMedic for Brain Tumor Segmentation

Kamnitsas, K., Ferrante, E., Parisot, S., Ledig, C., Nori, A. V., Criminisi, A., Rueckert, D., & Glocker, B. (2016) · Lecture Notes in Computer Science

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 346

Differential diagnosis of neurodegenerative diseases using structural MRI data

Koikkalainen, J., Rhodius-Meester, H., Tolonen, A., Barkhof, F., Tijms, B., Lemstra, A. W., Tong, T., Guerrero, R., Schuh, A., Ledig, C., et al. (2016) · NeuroImage: Clinical

Dementia and Cognitive Impairment ResearchArtificial Intelligence in Healthcare

Cited by 193

Automatic quantification of normal cortical folding patterns from fetal brain MRI

Wright, R., Kyriakopoulou, V., Ledig, C., Rutherford, M. A., Hajnal, J. V., Rueckert, D., & Aljabar, P. (2014) · NeuroImage

Medical Image Segmentation TechniquesFetal and Pediatric Neurological Disorders

Cited by 134

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting

Tong, T., Ledig, C., Guerrero, R., Schuh, A., Koikkalainen, J., Tolonen, A., Rhodius, H., Barkhof, F., Tijms, B., Lemstra, A. W., et al. (2017) · NeuroImage: Clinical

Dementia and Cognitive Impairment ResearchArtificial Intelligence in Healthcare

Cited by 54

Contusion segmentation from subjects with Traumatic Brain Injury: A random forest framework

Rao, A., Ledig, C., Newcombe, V., Menon, D., & Rueckert, D. (2014) · 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 18

MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions

Di Salvo, F., Doerrich, S., & Ledig, C. (2024) · arXiv

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 3