Maximilian Baust

3.3k total citations · 1 hit paper
33 papers, 1.5k citations indexed

About

Maximilian Baust is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Maximilian Baust has authored 33 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 9 papers in Computational Mechanics and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Maximilian Baust's work include Medical Image Segmentation Techniques (17 papers), 3D Shape Modeling and Analysis (6 papers) and Advanced Vision and Imaging (4 papers). Maximilian Baust is often cited by papers focused on Medical Image Segmentation Techniques (17 papers), 3D Shape Modeling and Analysis (6 papers) and Advanced Vision and Imaging (4 papers). Maximilian Baust collaborates with scholars based in Germany, United States and India. Maximilian Baust's co-authors include Nassir Navab, Slobodan Ilić, Miroslava Slavcheva, Tingying Peng, Katja Steiger, Iréne Esposito, Abhishek Vahadane, Amit Sethi, Anna Melissa Schlitter and Shadi Albarqouni and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Maximilian Baust

33 papers receiving 1.4k citations

Hit Papers

Structure-Preserving Color Normalization and Sparse Stain... 2016 2026 2019 2022 2016 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images
    2016 453 citations Abhishek Vahadane, Tingying Peng et al. IEEE Transactions on Medical Imaging profile →

Peers

Maximilian Baust
Diana Mateus France
Liansheng Wang China
Chenyu You United States
Andrea Schenk Germany
Caroline Essert France
Martin Urschler Austria
Tobias Heimann Germany
Roland Kwitt Austria
Ivo Wolf Germany
Shadrokh Samavi Iran
Diana Mateus France
Maximilian Baust
Citations per year, relative to Maximilian Baust Maximilian Baust (= 1×) peers Diana Mateus

Countries citing papers authored by Maximilian Baust

Since Specialization
Citations

This map shows the geographic impact of Maximilian Baust's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maximilian Baust with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maximilian Baust more than expected).

Fields of papers citing papers by Maximilian Baust

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maximilian Baust. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maximilian Baust. The network helps show where Maximilian Baust may publish in the future.

Co-authorship network of co-authors of Maximilian Baust

This figure shows the co-authorship network connecting the top 25 collaborators of Maximilian Baust. A scholar is included among the top collaborators of Maximilian Baust based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maximilian Baust. Maximilian Baust is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Slavcheva, Miroslava, Maximilian Baust, & Slobodan Ilić. (2020). Variational Level Set Evolution for Non-rigid 3D Reconstruction from a Single Depth Camera. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(8). 1–1. 18 indexed citations
2.
Esposito, Marco, Christoph Hennersperger, Laurent Demaret, et al.. (2019). Total Variation Regularization of Pose Signals With an Application to 3D Freehand Ultrasound. IEEE Transactions on Medical Imaging. 38(10). 2245–2258. 10 indexed citations
3.
Nekolla, Stephan G., et al.. (2019). Classification of Polar Maps from Cardiac Perfusion Imaging with Graph-Convolutional Neural Networks. Scientific Reports. 9(1). 7569–7569. 40 indexed citations
4.
Li, Wenqi, Fausto Milletarì, Daguang Xu, et al.. (2019). Privacy-Preserving Federated Brain Tumour Segmentation. Lecture notes in computer science. 11861. 133–141. 294 indexed citations
5.
Virga, Salvatore, et al.. (2018). Use the force: deformation correction in robotic 3D ultrasound. International Journal of Computer Assisted Radiology and Surgery. 13(5). 619–627. 23 indexed citations
6.
Slavcheva, Miroslava, Maximilian Baust, & Slobodan Ilić. (2018). SobolevFusion: 3D Reconstruction of Scenes Undergoing Free Non-rigid Motion. 2646–2655. 71 indexed citations
7.
Sharma, Kanishka, Christian Rupprecht, Anna Caroli, et al.. (2017). Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease. Scientific Reports. 7(1). 2049–2049. 133 indexed citations
8.
Slavcheva, Miroslava, Maximilian Baust, Daniel Cremers, & Slobodan Ilić. (2017). KillingFusion: Non-rigid 3D Reconstruction without Correspondences. 5474–5483. 110 indexed citations
9.
Rupprecht, Christian, Iro Laina, Robert DiPietro, et al.. (2017). Learning in an Uncertain World: Representing Ambiguity Through Multiple Hypotheses. 3611–3620. 81 indexed citations
10.
Baust, Maximilian, et al.. (2016). Vascular image registration techniques: A living review. Medical Image Analysis. 35. 1–17. 32 indexed citations
11.
Weinmann, Andreas, et al.. (2016). Joint Segmentation and Shape Regularization With a Generalized Forward–Backward Algorithm. IEEE Transactions on Image Processing. 25(7). 3384–3394. 2 indexed citations
12.
Albarqouni, Shadi, et al.. (2015). Multi-scale Graph-based Guided Filter for De-noising Cryo-Electron Tomographic Data. 17.1–17.10. 1 indexed citations
13.
Vahadane, Abhishek, Tingying Peng, Shadi Albarqouni, et al.. (2015). Structure-preserved color normalization for histological images. 1012–1015. 60 indexed citations
14.
Hennersperger, Christoph, et al.. (2015). Real-time uncertainty visualization for B-mode ultrasound. 5669. 33–40. 5 indexed citations
15.
Zettinig, Oliver, et al.. (2014). 3D Velocity Field and Flow Profile Reconstruction from Arbitrarily Sampled Doppler Ultrasound Data. Lecture notes in computer science. 17(Pt 2). 611–618. 1 indexed citations
16.
Peng, Tingying, Lichao Wang, Christine Bayer, et al.. (2014). Shading Correction for Whole Slide Image Using Low Rank and Sparse Decomposition. Lecture notes in computer science. 17(Pt 1). 33–40. 9 indexed citations
17.
Demirci, Stefanie, et al.. (2013). Disocclusion-based 2D–3D registration for aortic interventions. Computers in Biology and Medicine. 43(4). 312–322. 19 indexed citations
18.
Demirci, Stefanie, Lejing Wang, Christian Wachinger, et al.. (2011). 3D Stent Recovery from One X-Ray Projection. Lecture notes in computer science. 14(Pt 1). 178–185. 14 indexed citations
19.
Ahmadi, Seyed‐Ahmad, Maximilian Baust, Athanasios Karamalis, et al.. (2011). Midbrain Segmentation in Transcranial 3D Ultrasound for Parkinson Diagnosis. Lecture notes in computer science. 14(Pt 3). 362–369. 16 indexed citations
20.
Zikic, Darko, Maximilian Baust, Ali Kamen, & Nassir Navab. (2010). Generalization of Deformable Registration in Riemannian Sobolev Spaces. Lecture notes in computer science. 13(Pt 2). 586–593. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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