Shit, Suprosanna
University of Zurich
7 papers on CoChatORCID 0000-0003-4435-7207
Most cited papers
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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
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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
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Machine learning analysis of whole mouse brain vasculature
Todorov, M. I., Paetzold, J. C., Schoppe, O., Tetteh, G., Shit, S., Efremov, V., Todorov-Völgyi, K., Düring, M., Dichgans, M., Piraud, M., et al. (2020) · Nature Methods
Medical Image Segmentation TechniquesCell Image Analysis Techniques
Cited by 338
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clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
Shit, S., Paetzold, J. C., Sekuboyina, A., Ezhov, I., Unger, A., Zhylka, A., Pluim, J. P. W., Bauer, U., & Menze, B. H. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Medical Image Segmentation TechniquesAdvanced Neural Network Applications
Cited by 60
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vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation
Wittmann, B., Wattenberg, Y., Amiranashvili, T., Shit, S., & Menze, B. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning
Cited by 25
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Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging
Turgut, Ö., Müller, P., Hager, P., Shit, S., Starck, S., Menten, M. J., Martens, E., & Rueckert, D. (2025) · Medical Image Analysis
ECG Monitoring and AnalysisMachine Learning in Healthcare
Cited by 22
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A deep-learning framework reveals whole-body perturbations at cell level
Kaltenecker, D., Horvath, I., Al-Maskari, R., Chen, Y., Kolabas, Z. I., Hoeher, L., Todorov, M., Minde, D.-P., Kapoor, S., Turhan, S. G., et al. (2026) · Nature
Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics
Cited by 5
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