Fabian Isensee
German Cancer Research Center(DE)Heidelberg University(DE)DKFZ-ZMBH Alliance(DE)
Publications by Year
Research Areas
Radiomics and Machine Learning in Medical Imaging, Advanced Neural Network Applications, AI in cancer detection, COVID-19 diagnosis using AI, Medical Image Segmentation Techniques
Most-Cited Works
- → The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping(2020)3,653 cited
- → Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?(2018)2,134 cited
- → The Medical Segmentation Decathlon(2022)1,122 cited
- → The Liver Tumor Segmentation Benchmark (LiTS)(2022)1,081 cited
- → CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation(2020)746 cited
- → Automated brain extraction of multisequence MRI using artificial neural networks(2019)665 cited
- → Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation(2019)583 cited
- → Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study(2019)425 cited
- → nnU-Net: Self-adapting Framework for U-Net-Based Medical Image\n Segmentation(2018)390 cited
- → Metrics reloaded: recommendations for image analysis validation(2024)351 cited