D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index 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. Citations Publications World Ranking National Ranking
Computer Science D-index 39 Citations 5,865 207 World Ranking 4784 National Ranking 288

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Surgery

Danail Stoyanov mostly deals with Artificial intelligence, Computer vision, Robot, Imaging phantom and Laparoscopic surgery. His studies deal with areas such as Machine learning and Specular highlight as well as Artificial intelligence. The study incorporates disciplines such as Invasive surgery and Soft tissue in addition to Computer vision.

His work carried out in the field of Invasive surgery brings together such families of science as Tracking and Feature. Danail Stoyanov combines subjects such as Motion estimation and Cognitive skill with his study of Robot. His Imaging phantom research incorporates themes from Surface finish, Image and Robotic surgery.

His most cited work include:

  • Surgical device with an end effector assembly and system for monitoring of tissue before and after a surgical procedure (249 citations)
  • Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery. (205 citations)
  • Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge (158 citations)

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

His main research concerns Artificial intelligence, Computer vision, Segmentation, Imaging phantom and Deep learning. His Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition. He has included themes like Invasive surgery and Robustness in his Computer vision study.

His Segmentation research is mostly focused on the topic Image segmentation. His Deep learning study frequently draws connections to adjacent fields such as Benchmark. Much of his study explores Convolutional neural network relationship to Optical flow.

He most often published in these fields:

  • Artificial intelligence (62.35%)
  • Computer vision (43.37%)
  • Segmentation (12.65%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (62.35%)
  • Computer vision (43.37%)
  • Segmentation (12.65%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Segmentation, Deep learning and Pattern recognition. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Colonoscopy and Machine learning. His Computer vision study deals with Surgical instrument intersecting with Parallel processing.

His work deals with themes such as Iterative reconstruction and Robotic surgery, which intersect with Segmentation. His study in Deep learning is interdisciplinary in nature, drawing from both Optical flow, Ground truth, Imaging phantom and Robustness. His research in Pattern recognition intersects with topics in Autoencoder, Point cloud, Representation and Inference.

Between 2019 and 2021, his most popular works were:

  • The challenges of deploying artificial intelligence models in a rapidly evolving pandemic (14 citations)
  • 2018 Robotic Scene Segmentation Challenge (13 citations)
  • Surgical spectral imaging (12 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Surgery

Danail Stoyanov spends much of his time researching Artificial intelligence, Computer vision, Deep learning, Segmentation and Machine learning. His biological study spans a wide range of topics, including Imaging phantom, Cadaver and Pattern recognition. Danail Stoyanov has researched Computer vision in several fields, including Convolutional neural network and Synthetic data.

His Deep learning research includes themes of White light, Ground truth, Feature extraction, Robustness and Visualization. In general Segmentation, his work in Scene segmentation is often linked to Set linking many areas of study. His Machine learning study combines topics from a wide range of disciplines, such as Modality, Spectral imaging, Hyperspectral imaging and Multispectral image.

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

Surgical device with an end effector assembly and system for monitoring of tissue before and after a surgical procedure

Shobhit Arya;Neil T. Clancy;Daniel S. Elson;George B. Hanna.
(2016)

462 Citations

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery.

Lena Maier-Hein;Peter Mountney;Adrien Bartoli;Haytham Elhawary.
Medical Image Analysis (2013)

239 Citations

Real-time stereo reconstruction in robotically assisted minimally invasive surgery

Danail Stoyanov;Marco Visentini Scarzanella;Philip Pratt;Guang-Zhong Yang.
medical image computing and computer assisted intervention (2010)

212 Citations

Surgical data science: Enabling next-generation surgery

Lena Maier-Hein;S. Swaroop Vedula;Stefanie Speidel;Nassir Navab;Nassir Navab.
arXiv: Computers and Society (2017)

188 Citations

Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge

Jorge Bernal;Nima Tajkbaksh;Francisco Javier Sanchez;Bogdan J. Matuszewski.
IEEE Transactions on Medical Imaging (2017)

186 Citations

Three-Dimensional Tissue Deformation Recovery and Tracking

Peter Mountney;Danail Stoyanov;Guang-Zhong Yang.
IEEE Signal Processing Magazine (2010)

176 Citations

Soft-tissue motion tracking and structure estimation for robotic assisted MIS procedures

Danail Stoyanov;George P. Mylonas;Fani Deligianni;Ara Darzi.
medical image computing and computer assisted intervention (2005)

168 Citations

Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions.

Yohannes Kassahun;Bingbin Yu;Abraham Temesgen Tibebu;Danail Stoyanov.
computer assisted radiology and surgery (2016)

144 Citations

Simultaneous stereoscope localization and soft-tissue mapping for minimal invasive surgery

Peter Mountney;Danail Stoyanov;Andrew Davison;Guang-Zhong Yang.
medical image computing and computer assisted intervention (2006)

131 Citations

Surgical data science for next-generation interventions.

Lena Maier-Hein;Swaroop S. Vedula;Stefanie Speidel;Nassir Navab;Nassir Navab.
Nature Biomedical Engineering (2017)

129 Citations

Best Scientists Citing Danail Stoyanov

Frederick E. Shelton

Frederick E. Shelton

Johnson & Johnson (United States)

Publications: 257

Guang-Zhong Yang

Guang-Zhong Yang

Shanghai Jiao Tong University

Publications: 75

Jerome R. Morgan

Jerome R. Morgan

Johnson & Johnson (United States)

Publications: 57

Lena Maier-Hein

Lena Maier-Hein

German Cancer Research Center

Publications: 55

Nassir Navab

Nassir Navab

Technical University of Munich

Publications: 50

Jeffrey S. Swayze

Jeffrey S. Swayze

Johnson & Johnson (United States)

Publications: 36

Qi Dou

Qi Dou

Chinese University of Hong Kong

Publications: 34

Adrien Bartoli

Adrien Bartoli

University of Clermont Auvergne

Publications: 33

Pheng-Ann Heng

Pheng-Ann Heng

Chinese University of Hong Kong

Publications: 33

Sebastien Ourselin

Sebastien Ourselin

King's College London

Publications: 29

Tom Vercauteren

Tom Vercauteren

King's College London

Publications: 27

Chester O. Baxter

Chester O. Baxter

Johnson & Johnson (United States)

Publications: 27

Pierre Jannin

Pierre Jannin

University of Rennes 1

Publications: 25

Max Q.-H. Meng

Max Q.-H. Meng

Southern University of Science and Technology

Publications: 21

Russell H. Taylor

Russell H. Taylor

Johns Hopkins University

Publications: 21

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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