Patrick Ferdinand Christ

University of Zurich — Switzerland

Medicine · Health Sciences

11h-index4.2kcitations19works12.52yr avg
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Research Topics

Radiomics and Machine Learning in Medical Imaging(11), Advanced Neural Network Applications(6), AI in cancer detection(4), Medical Image Segmentation Techniques(3), MRI in cancer diagnosis(3)

Publications19 total

MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision
Open Access CRIS of the University of Bern·2024Open Access
<i>MedShapeNet</i> – a large-scale dataset of 3D medical shapes for computer vision
Biomedizinische Technik/Biomedical Engineering·2024· 25 citedOpen Access
The Liver Tumor Segmentation Benchmark (LiTS)
Medical Image Analysis·2022· 1.0k citedOpen Access
The Medical Segmentation Decathlon
Nature Communications·2022· 1.1k citedOpen Access
The Medical Segmentation Decathlon
arXiv (Cornell University)·2021· 10 citedOpen Access
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
arXiv (Cornell University)·2019· 715 citedOpen Access
The Liver Tumor Segmentation Benchmark (LiTS)
Rare & Special e-Zone (The Hong Kong University of Science and Technology)·2019· 251 citedOpen Access
Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on <sup>68</sup>Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods
Contrast Media & Molecular Imaging·2018· 130 citedOpen Access
Diabetes60 — Inferring Bread Units From Food Images Using Fully Convolutional Neural Networks
2017· 28 citedOpen Access
Automated Unsupervised Segmentation of Liver Lesions in CT scans via Cahn-Hilliard Phase Separation
arXiv (Cornell University)·2017· 8 citedOpen Access
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D Convolutional Neural Networks
2017· 22 cited
Die Hauptkomponentenanalyse von ADC-Histogrammen als prädiktiver Faktor im HCC
RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren·2017
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks
arXiv (Cornell University)·2017· 184 citedOpen Access
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks
arXiv (Cornell University)·2017· 10 citedOpen Access
Convolutional Neural Networks for Classification and Segmentation of Medical Images
mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich)·2017· 1 citedOpen Access
Nachhaltigkeit im industriellen Umfeld : Studentische Fachkonferenz 2016
2017
W-Net for Whole-Body Bone Lesion Detection on $$^{68}$$ Ga-Pentixafor PET/CT Imaging of Multiple Myeloma Patients
Lecture notes in computer science·2017· 6 cited
Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields
Lecture notes in computer science·2016· 627 citedOpen Access
Human-Drone-Interaction: A Case Study to Investigate the Relation Between Autonomy and User Experience
Lecture notes in computer science·2016· 15 cited

Frequent Co-authors

Bjoern Menze(13), Patrick Bilic(7), Florian Ettlinger(7), Georgios Kaissis(6), Jana Lipková(6), Michela Antonelli(5), Spyridon Bakas(5), Eugene Vorontsov(5), M. Jorge Cardoso(5), Markus Rempfler(5), Seyed‐Ahmad Ahmadi(5), Fabian Isensee(4), Yuanfeng Ji(4), Fucang Jia(4), Ildoo Kim(4), Dorit Merhof(4), Akshay Pai(4), Mathias Perslev(4), Oliver Rippel(4), Ignacio Sarasúa(4)