D-Index & Metrics Best Publications

Joachim Hornegger

University of Erlangen-Nuremberg
Germany

Computer Science

Germany

2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 59 Citations 14,630 513 World Ranking 2239 National Ranking 98

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Germany Leader Award

Overview

What is he best known for?

The fields of study Joachim Hornegger is best known for:

Magnetic resonance imaging
Angiography
Fluoroscopy

His study on Mathematical optimization is interrelated to topics such as Quadratic programming and Subgradient method. Joachim Hornegger performs multidisciplinary study in Quadratic programming and Convex optimization in his work. He brings together Subgradient method and Convex optimization to produce work in his papers. His Artificial intelligence study typically links adjacent topics like Data set. Computer vision is frequently linked to Stereoscopy in his study. While working on this project, Joachim Hornegger studies both Iterative reconstruction and Imaging phantom. Joachim Hornegger undertakes interdisciplinary study in the fields of Imaging phantom and Iterative reconstruction through his research. His Radiology study frequently draws connections to other fields, such as Stent. His multidisciplinary approach integrates Stent and Angiography in his work.

His most cited work include:

Wavelet Based Noise Reduction in CT-Images Using Correlation Analysis (128 citations)
Discrete tomography by convex–concave regularization and D.C. programming (102 citations)
Comparative Validation of Single-Shot Optical Techniques for Laparoscopic 3-D Surface Reconstruction (90 citations)

What are the main themes of his work throughout his whole career to date

His Image (mathematics) study is focused on Image quality, Noise (video) and Image registration. His Image (mathematics) research extends to the thematically linked field of Noise (video). Joachim Hornegger combines Artificial intelligence and Machine learning in his research. In his articles, Joachim Hornegger combines various disciplines, including Machine learning and Artificial intelligence. His Computer vision study frequently links to adjacent areas such as Filter (signal processing). Filter (signal processing) and Computer vision are commonly linked in his work. He carries out multidisciplinary research, doing studies in Radiology and Iterative reconstruction. In his research, he undertakes multidisciplinary study on Iterative reconstruction and Radiology. He combines topics linked to Optics with his work on Imaging phantom.

Joachim Hornegger most often published in these fields:

Artificial intelligence (82.35%)
Computer vision (61.76%)
Radiology (47.06%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Split-spectrum amplitude-decorrelation angiography with optical coherence tomography

Yali Jia;Ou Tan;Jason Tokayer;Benjamin Potsaid.
Optics Express (2012)

1722 Citations

Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets

T. Heimann;B. van Ginneken;M.A. Styner;Y. Arzhaeva.
IEEE Transactions on Medical Imaging (2009)

1068 Citations

Quantitative optical coherence tomography angiography of vascular abnormalities in the living human eye

Yali Jia;Steven T. Bailey;Thomas S. Hwang;Scott M. McClintic.
Proceedings of the National Academy of Sciences of the United States of America (2015)

614 Citations

Glaucoma risk index: Automated glaucoma detection from color fundus images

Rüdiger Bock;Jörg Meier;László G. Nyúl;Joachim Hornegger.
Medical Image Analysis (2010)

406 Citations

Motion correction in optical coherence tomography volumes on a per A-scan basis using orthogonal scan patterns

Martin F. Kraus;Benjamin Potsaid;Markus A. Mayer;Ruediger Bock.
Biomedical Optics Express (2012)

398 Citations

Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database

Jan Odstrcilik;Radim Kolar;Attila Budai;Joachim Hornegger.
Iet Image Processing (2013)

371 Citations

Robust Vessel Segmentation in Fundus Images

Attila Budai;Rüdiger Bock;Andreas K. Maier;Joachim Hornegger.
International Journal of Biomedical Imaging (2013)

369 Citations

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015

Nassir Navab;Joachim Hornegger;William M. Wells;Alejandro F. Frangi.
(2015)

366 Citations

Fast GPU-Based CT Reconstruction using the Common Unified Device Architecture (CUDA)

H. Scherl;B. Keck;M. Kowarschik;J. Hornegger.
ieee nuclear science symposium (2007)

245 Citations

Quantitative Accuracy of Clinical 99mTc SPECT/CT Using Ordered-Subset Expectation Maximization with 3-Dimensional Resolution Recovery, Attenuation, and Scatter Correction

Johannes Zeintl;Alexander Hans Vija;Amos Yahil;Joachim Hornegger.
The Journal of Nuclear Medicine (2010)

209 Citations

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Joachim Hornegger

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Research.com Recognitions

Awards & Achievements

Overview

What is he best known for?

The fields of study Joachim Hornegger is best known for:

His most cited work include:

What are the main themes of his work throughout his whole career to date

Joachim Hornegger most often published in these fields:

Best Publications

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