Schnabel, Julia A.

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Lekadir, K., Frangi, A. F., Porras, A. R., Glocker, B., Cintas, C., Langlotz, C. P., Weicken, E., Asselbergs, F. W., Prior, F., Collins, G. S., et al. (2025) · BMJ

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 957

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study

Wagner, S. J., Reisenbüchler, D., West, N. P., Niehues, J. M., Zhu, J., Foersch, S., Veldhuizen, G. P., Quirke, P., Grabsch, H. I., van den Brandt, P. A., et al. (2023) · Cancer Cell

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 275

Towards realtime multimodal fusion for image-guided interventions using self-similarities

Heinrich, M. P., Jenkinson, M., Papież, B. W., Brady, S. M., & Schnabel, J. A. (2013) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesAdvanced Image and Video Retrieval Techniques

Cited by 176

Global and Local Interpretability for Cardiac MRI Classification

Clough, J. R., Oksuz, I., Puyol-Antón, E., Ruijsink, B., King, A. P., & Schnabel, J. A. (2019) · Lecture Notes in Computer Science

Explainable Artificial Intelligence (XAI)Cardiac Imaging and Diagnostics

Cited by 73

Advances and challenges in deformable image registration: From image fusion to complex motion modelling

Schnabel, J. A., Heinrich, M. P., Papież, B. W., & Brady, S. J. M. (2016) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 60

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging

Meng, Q., Housden, J., Matthew, J., Rueckert, D., Schnabel, J. A., Kainz, B., Sinclair, M., Zimmer, V., Hou, B., Rajchl, M., et al. (2019) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 52

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time

Matthew, J., Skelton, E., Day, T. G., Zimmer, V. A., Gomez, A., Wheeler, G., Toussaint, N., Liu, T., Budd, S., Lloyd, K., et al. (2022) · Prenatal Diagnosis

Artificial Intelligence in Healthcare and EducationPrenatal Screening and Diagnostics

Cited by 41

Towards Whole Placenta Segmentation at Late Gestation Using Multi-view Ultrasound Images

Zimmer, V. A., Gomez, A., Skelton, E., Toussaint, N., Zhang, T., Khanal, B., Wright, R., Noh, Y., Ho, A., Matthew, J., et al. (2019) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 20

Image Analysis: Understanding and Mitigating Batch Effects in Histopathology

Gindra, R. H., Boushehri, S. S., Wagner, S. J., Tran, M., Winter, D. J. E., Schnabel, J. A., Saur, D., Marr, C., & Peng, T. (2025) · Trillium Pathology

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 2