Criminisi, Antonio

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 6,781

Region Filling and Object Removal by Exemplar-Based Image Inpainting

Criminisi, A., Perez, P., & Toyama, K. (2004) · IEEE Transactions on Image Processing

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 3,258

Decision forests: A unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning

Criminisi, A., Shotton, J., & Konukoglu, E. (2012) · Foundations and Trends® in Computer Graphics and Vision

Machine Learning and AlgorithmsNeural Networks and Applications

Cited by 677

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

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Ioannou, Y., Robertson, D., Cipolla, R., & Criminisi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 321

GeoS: Geodesic Image Segmentation

Criminisi, A., Sharp, T., & Blake, A. (2008) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 277

Decision Forests for Tissue-Specific Segmentation of High-Grade Gliomas in Multi-channel MR

Zikic, D., Glocker, B., Konukoglu, E., Criminisi, A., Demiralp, C., Shotton, J., Thomas, O. M., Das, T., Jena, R., & Price, S. J. (2012) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 276

Autofocus Layer for Semantic Segmentation

Qin, Y., Kamnitsas, K., Ancha, S., Nanavati, J., Cottrell, G., Criminisi, A., & Nori, A. (2018) · arXiv

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 135

Autofocus Layer for Semantic Segmentation

Qin, Y., Kamnitsas, K., Ancha, S., Nanavati, J., Cottrell, G., Criminisi, A., & Nori, A. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 135

Encoding atlases by randomized classification forests for efficient multi-atlas label propagation

Zikic, D., Glocker, B., & Criminisi, A. (2014) · Medical Image Analysis

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 81

Smartphone camera based assessment of adiposity: a validation study

Majmudar, M. D., Chandra, S., Yakkala, K., Kennedy, S., Agrawal, A., Sippel, M., Ramu, P., Chaudhri, A., Smith, B., Criminisi, A., et al. (2022) · npj Digital Medicine

Body Composition Measurement TechniquesAdvanced Neural Network Applications

Cited by 75

GeoF: Geodesic Forests for Learning Coupled Predictors

Kontschieder, P., Kohli, P., Shotton, J., & Criminisi, A. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 63

Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement

Tanno, R., Worrall, D., Kaden, E., Ghosh, A., Grussu, F., Bizzi, A., Sotiropoulos, S. N., Criminisi, A., & Alexander, D. C. (2019) · arXiv

Advanced Image Processing TechniquesImage and Signal Denoising Methods

Cited by 30

Discriminative segmentation-based evaluation through shape dissimilarity

Konukoglu, E., Glocker, B., Ye, D. H., Criminisi, A., & Pohl, K. M. (2012) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 14

Modeling health risks using neural network ensembles

Smith, B. M., Criminisi, A., Sorek, N., Harari, Y., Sood, N., & Heymsfield, S. B. (2024) · PLOS ONE

Artificial Intelligence in HealthcareMachine Learning in Healthcare

Cited by 5