Isensee, Fabian

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., et al. (2020) · Radiology

Radiomics and Machine Learning in Medical ImagingImage Retrieval and Classification Techniques

Cited by 4,177

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?

Bernard, O., Lalande, A., Zotti, C., Cervenansky, F., Yang, X., Heng, P.-A., Cetin, I., Lekadir, K., Camara, O., Gonzalez Ballester, M. A., et al. (2018) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 2,431

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,384

No New-Net

Isensee, F., Kickingereder, P., Wick, W., Bendszus, M., & Maier-Hein, K. H. (2019) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 341

Understanding metric-related pitfalls in image analysis validation

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 241

Common Limitations of Image Processing Metrics: A Picture Story

Reinke, A., Tizabi, M. D., Sudre, C. H., Eisenmann, M., Rädsch, T., Baumgartner, M., Acion, L., Antonelli, M., Arbel, T., Bakas, S., et al. (2021) · arXiv

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 126

Metrics reloaded: Recommendations for image analysis validation

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., et al. (2022) · arXiv

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 59

The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT

Heller, N., Isensee, F., Trofimova, D., Tejpaul, R., Zhao, Z., Chen, H., Wang, L., Golts, A., Khapun, D., Shats, D., et al. (2023) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 35

Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks

Pflüger, I., Wald, T., Isensee, F., Schell, M., Meredig, H., Schlamp, K., Bernhardt, D., Brugnara, G., Heußel, C. P., Debus, J., et al. (2022) · Neuro-Oncology Advances

Brain Tumor Detection and ClassificationBrain Metastases and Treatment

Cited by 31

Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation

Kirscher, T., Bujotzek, M., Kirchhoff, Y., Rokuss, M., Isensee, F., Kahl, K.-C., Kovacs, B., & Maier-Hein, K. (2026) · arXiv

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 0