D-Index & Metrics Best Publications

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 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 59 Citations 24,629 461 World Ranking 2180 National Ranking 125

Research.com Recognitions

Awards & Achievements

2021 - IEEE EMBS Technical Achievement Award For pioneering contributions in model-based image computing and image-based computational modelling in medicine with clinical and innovation impact

2021 - MICCAI Fellow For outstanding contributions to computational medical imaging

2020 - SPIE Fellow for achievements in statistical methods in medical image computing and image-based computational modelling

2014 - IEEE Fellow For contributions to medical image analysis and image-based computational physiology

2013 - EAMBES Fellow

2006 - IEEE EMBS Early Career Award for outstanding contributions to medical image computing, especially cardiovascular and cerebrovascular image analysis using model- and registration-based methods

2002 - Ramón y Cajal Research Fellowship

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Internal medicine
  • Statistics

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Aneurysm and Active shape model. His Artificial intelligence research incorporates themes from Machine learning, Parametric statistics and Atlas. His Computer vision research is multidisciplinary, incorporating perspectives in Algorithm and Energy functional.

The Pattern recognition study combines topics in areas such as Object and Genetic algorithm. His research integrates issues of Odds ratio, Blood flow, Internal medicine, Vascular disease and Hemodynamics in his study of Aneurysm. The study incorporates disciplines such as Image segmentation and Active appearance model in addition to Active shape model.

His most cited work include:

  • Two-dimensional PCA: a new approach to appearance-based face representation and recognition (2969 citations)
  • Muliscale Vessel Enhancement Filtering (2736 citations)
  • KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition (750 citations)

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

Alejandro F. Frangi mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Biomedical engineering. Artificial intelligence is represented through his Active shape model, Image segmentation, Image registration, Feature extraction and Statistical model research. The Computer vision study which covers Cardiac resynchronization therapy that intersects with Ventricle.

Pattern recognition is closely attributed to Facial recognition system in his study. His Biomedical engineering research includes elements of Aneurysm and Hemodynamics. His Aneurysm research integrates issues from Stent and Angiography.

He most often published in these fields:

  • Artificial intelligence (51.87%)
  • Computer vision (33.12%)
  • Pattern recognition (22.50%)

What were the highlights of his more recent work (between 2015-2022)?

  • Artificial intelligence (51.87%)
  • Pattern recognition (22.50%)
  • Segmentation (15.63%)

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

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Segmentation, Computer vision and Magnetic resonance imaging. His study in Deep learning, Image segmentation, Image, Mixture model and Outlier is carried out as part of his studies in Artificial intelligence. His biological study deals with issues like Ejection fraction, which deal with fields such as Both ventricles.

His study on Cut is often connected to Pipeline as part of broader study in Segmentation. His work deals with themes such as Field, Polygon mesh and Interpolation, which intersect with Computer vision. His Magnetic resonance imaging research includes themes of Ground truth, Cerebral blood flow and Sensitivity.

Between 2015 and 2022, his most popular works were:

  • A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging. (147 citations)
  • A multi-center milestone study of clinical vertebral CT segmentation (66 citations)
  • Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images (49 citations)

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

  • Artificial intelligence
  • Internal medicine
  • Statistics

Alejandro F. Frangi mainly focuses on Artificial intelligence, Pattern recognition, Segmentation, Magnetic resonance imaging and Medical imaging. Artificial intelligence is often connected to Computer vision in his work. His work deals with themes such as Data mining, Pixel, Image Quantification, Ventricular endocardium and Synthetic data, which intersect with Pattern recognition.

His work investigates the relationship between Segmentation and topics such as Algorithm that intersect with problems in Transformation, Segmentation-based object categorization, Scale-space segmentation, Image segmentation and Focus. His work carried out in the field of Magnetic resonance imaging brings together such families of science as Ground truth, Heart chamber and Medical physics. His Medical imaging study combines topics from a wide range of disciplines, such as Feature extraction, Image, Data science and Histopathology.

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

Two-dimensional PCA: a new approach to appearance-based face representation and recognition

Jian Yang;D. Zhang;A.F. Frangi;Jing-yu Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

4728 Citations

Muliscale Vessel Enhancement Filtering

Alejandro F. Frangi;Wiro J. Niessen;Koen L. Vincken;Max A. Viergever.
medical image computing and computer assisted intervention (1998)

4598 Citations

KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition

Jian Yang;A.F. Frangi;Jing-Yu Yang;David Zhang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)

1052 Citations

Three-dimensional modeling for functional analysis of cardiac images, a review

A.F. Frangi;W.J. Niessen;M.A. Viergever.
IEEE Transactions on Medical Imaging (2001)

794 Citations

Active shape model segmentation with optimal features

B. van Ginneken;A.F. Frangi;J.J. Staal;B.M. ter Haar Romeny.
IEEE Transactions on Medical Imaging (2002)

721 Citations

Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity

J.R. Cebral;M.A. Castro;S. Appanaboyina;C.M. Putman.
IEEE Transactions on Medical Imaging (2005)

678 Citations

Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration

D. Rueckert;A.F. Frangi;J.A. Schnabel.
IEEE Transactions on Medical Imaging (2003)

570 Citations

Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling

A.F. Frangi;D. Rueckert;J.A. Schnabel;W.J. Niessen.
IEEE Transactions on Medical Imaging (2002)

539 Citations

Model-based quantitation of 3-D magnetic resonance angiographic images

A.F. Frangi;W.J. Niessen;R.M. Hoogeveen;T. van Walsum.
IEEE Transactions on Medical Imaging (1999)

491 Citations

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

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

366 Citations

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