World's Best Scientists 2026 revealed!

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Computer Science

D-Index
30
Citations
8601
World Ranking
13841
National Ranking
667

Overview

Christian Wachinger is affiliated with the Technical University of Munich in Germany. Their research spans multiple areas within medicine and computer science, with significant contributions in neuroimaging and medical image analysis.

Wachinger's research publication record includes papers focused on topics such as medical image segmentation, neuroimaging bias correction, and shape analysis in neurological disorders. Recent notable publications include:

  • The Medical Segmentation Decathlon, 2022, Nature Communications
  • The Liver Tumor Segmentation Benchmark (LiTS), 2022, Medical Image Analysis
  • Detect and correct bias in multi-site neuroimaging datasets, 2020, Medical Image Analysis
  • Increased hippocampal shape asymmetry and volumetric ventricular asymmetry in autism spectrum disorder, 2020, NeuroImage Clinical
  • 'Squeeze & excite' guided few-shot segmentation of volumetric images, 2020, PubMed

Frequent coauthors in Wachinger's work include:

  • Sebastian Pölsterl
  • Fabian Bongratz
  • Anne-Marie Rickmann
  • Ignacio Sarasúa
  • Tom Nuno Wolf

Their publications are often featured in venues such as:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Lecture Notes in Computer Science
  • Scientific Reports
  • IEEE Transactions on Medical Imaging

Wachinger has authored work published by Springer Science+Business Media, including the 2023 book Shape in Medical Imaging.

The primary fields of study include:

  • Medicine
  • Computer Science

Within these fields, their work addresses several subfields:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Psychiatry and Mental Health

The main research topics covered by Wachinger encompass:

  • Advanced Neuroimaging Techniques and Applications
  • Medical Image Segmentation Techniques
  • Functional Brain Connectivity Studies
  • Radiomics and Machine Learning in Medical Imaging
  • Machine Learning in Healthcare
  • Dementia and Cognitive Impairment Research
  • Advanced MRI Techniques and Applications

Best Publications

  • The Liver Tumor Segmentation Benchmark (LiTS)

    Patrick Bilic;Patrick Ferdinand Christ;Eugene Vorontsov;Grzegorz Chlebus

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Concurrent Spatial and Channel ‘Squeeze & Excitation’ in Fully Convolutional Networks

    Abhijit Guha Roy;Nassir Navab;Christian Wachinger

  • ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks.

    Abhijit Guha Roy;Sailesh Conjeti;Sri Phani Krishna Karri;Debdoot Sheet

  • Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks

    Abhijit Guha Roy;Nassir Navab;Christian Wachinger

  • DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

    Christian Wachinger;Martin Reuter;Tassilo Klein

  • Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

    Esther E. Bron;Marion Smits;Wiesje M. van der Flier;Hugo Vrenken

  • QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy.

    Abhijit Guha Roy;Sailesh Conjeti;Sailesh Conjeti;Nassir Navab;Nassir Navab;Christian Wachinger

  • BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning.

    Abhijit Guha Roy;Shayan Siddiqui;Sebastian Pölsterl;Nassir Navab

  • 'Squeeze & excite' guided few-shot segmentation of volumetric images.

    Abhijit Guha Roy;Shayan Siddiqui;Sebastian Pölsterl;Nassir Navab;Nassir Navab

  • Entropy and Laplacian Images: Structural Representations for Multi-Modal Registration

    Christian Wachinger;Nassir Navab

  • BrainPrint: a discriminative characterization of brain morphology.

    Christian Wachinger;Polina Golland;William S. Kremen;Bruce Fischl

  • The Liver Tumor Segmentation Benchmark (LiTS)

    Unknown

  • Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks

    Abhijit Guha Roy;Nassir Navab;Christian Wachinger

  • Domain adaptation for Alzheimer's disease diagnostics.

    Christian Wachinger;Martin Reuter

  • Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control.

    Abhijit Guha Roy;Sailesh Conjeti;Nassir Navab;Nassir Navab;Christian Wachinger

  • Blockface histology with optical coherence tomography: A comparison with Nissl staining

    Caroline Magnain;Jean C. Augustinack;Martin Reuter;Martin Reuter;Christian Wachinger;Christian Wachinger

  • Detect and correct bias in multi-site neuroimaging datasets.

    Christian Wachinger;Anna Rieckmann;Sebastian Pölsterl

  • Manifold learning for image-based breathing gating in ultrasound and MRI

    Christian Wachinger;Mehmet Yigitsoy;Erik-Jan Rijkhorst;Nassir Navab

  • Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data

    Abhijit Guha Roy;Abhijit Guha Roy;Sailesh Conjeti;Debdoot Sheet;Amin Katouzian

  • Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling

    Abhijit Guha Roy;Sailesh Conjeti;Nassir Navab;Christian Wachinger

  • Three-dimensional ultrasound mosaicing

    Christian Wachinger;Wolfgang Wein;Nassir Navab

  • Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks

    Abhijit Guha Roy;Nassir Navab;Christian Wachinger

Frequent Co-Authors

Nassir Navab
Nassir Navab Technical University of Munich
Martin Reuter
Martin Reuter University of Bonn
Bruce Fischl
Bruce Fischl Harvard University
Georg Langs
Georg Langs Medical University of Vienna
Annette Peters
Annette Peters Ludwig-Maximilians-Universität München
Kwangsik Nho
Kwangsik Nho Indiana University
Ben Glocker
Ben Glocker Imperial College London
Gerd Schulte-Körne
Gerd Schulte-Körne Ludwig-Maximilians-Universität München

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