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Nahum Kiryati

Nahum Kiryati

D-Index & Metrics

Computer Science

D-Index
45
Citations
8651
World Ranking
7179
National Ranking
116

Overview

Nahum Kiryati is affiliated with Tel Aviv University in Israel and has contributed extensively to research at the intersection of medicine and computer science. Their work focuses primarily on medical imaging, advanced image processing, and applications of artificial intelligence in healthcare.

The main fields of study associated with their research are Medicine and Computer Science. More specifically, key subfields include Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Health Informatics, and Surgery.

Key topics covered in Nahum Kiryati's publications reflect a focus on radiomics and machine learning in medical imaging, AI in cancer detection, advanced image processing techniques, advanced MRI techniques and applications, advanced neural network applications, image and signal denoising methods, and COVID-19 diagnosis using AI.

Frequent coauthors collaborating with Nahum Kiryati include:

  • Arnaldo Mayer
  • Eli Konen
  • Miri Sklair-Levy
  • Ilya Nelkenbaum
  • Chen-Han Tsai

Among notable publication venues, Nahum Kiryati has appeared multiple times in the Journal of Imaging, arXiv (Cornell University), and Lecture Notes in Computer Science. Other venues include PLoS ONE and the International Journal of Computer Assisted Radiology and Surgery.

The following are selected recent papers by Nahum Kiryati and close collaborators:

  • "Dataset Growth in Medical Image Analysis Research," 2021, Journal of Imaging
  • "Knee Injury Detection using MRI with Efficiently-Layered Network (ELNet)," 2020, arXiv (Cornell University)
  • "Motion magnification analysis of microscopy videos of biological cells," 2020, PLoS ONE
  • "Anisotropic neural deblurring for MRI acceleration," 2021, International Journal of Computer Assisted Radiology and Surgery
  • "Detecting Cocircular Subsets of a Spherical Set of Points," 2022, Journal of Imaging

Nahum Kiryati's work frequently engages with machine learning methods and neural networks to improve diagnostic accuracy and enhance imaging techniques, supporting applications such as cancer detection and accelerated MRI processes. The integration of AI in medical imaging is a recurrent theme throughout their body of research.

Best Publications

  • A probabilistic Hough transform

    N. Kiryati;Y. Eldar;A. M. Bruckstein

  • Range imaging with adaptive color structured light

    D. Caspi;N. Kiryati;J. Shamir

  • Skeletonization via distance maps and level sets

    Ron Kimmel;Doron Shaked;Nahum Kiryati;Alfred M. Bruckstein

  • Depth from Defocus vs. Stereo: How Different Really Are They?

    Yoav Y. Schechner;Nahum Kiryati

  • Texture mapping using surface flattening via multidimensional scaling

    G. Zigelman;R. Kimmel;N. Kiryati

  • MRI inter-slice reconstruction using super-resolution

    H. Greenspan;G. Oz;N. Kiryati;S. Peled

  • Multi-view Scene Flow Estimation: A View Centered Variational Approach

    Tali Basha;Yael Moses;Nahum Kiryati

  • Separation of Transparent Layers using Focus

    Yoav Y. Schechner;Nahum Kiryati;Ronen Basri

  • Toward optimal structured light patterns

    Eli Horn;Nahum Kiryati

  • Polarization and statistical analysis of scenes containing a semireflector.

    Yoav Y. Schechner;Joseph Shamir;Nahum Kiryati

  • Sub-pixel distance maps and weighted distance transforms

    Ron Kimmel;Nahum Kiryati;Alfred M. Bruckstein

  • Image Deblurring in the Presence of Impulsive Noise

    Leah Bar;Nahum Kiryati;Nir Sochen

  • Detecting Symmetry in Grey Level Images: The Global Optimization Approach

    Nahum Kiryati;Yossi Gofman

  • Polarization-based decorrelation of transparent layers: The inclination angle of an invisible surface

    Y.Y. Schechner;J. Shamir;N. Kiryati

  • Deblurring of Color Images Corrupted by Impulsive Noise

    L. Bar;A. Brook;N. Sochen;N. Kiryati

  • Image deblurring in the presence of salt-and-pepper noise

    Leah Bar;Nir Sochen;Nahum Kiryati

  • Deriving Stopping Rules for the Probabilistic Hough Transform by Sequential Analysis

    D. Shaked;O. Yaron;N. Kiryati

  • Apparatus and methods for the detection of abnormal motion in a video stream

    Nahum Kiryati;Tamar Riklin-Raviv;Yan Ivanchenko;Shay Rochel

  • Semi-blind image restoration via Mumford-Shah regularization

    L. Bar;N. Sochen;N. Kiryati

  • Estimating shortest paths and minimal distances on digitized three-dimensional surfaces

    Nahum Kiryati;Gabor Székely

  • Detecting symmetry in grey level images: the global optimization approach

    Y. Gofman;N. Kiryati

Frequent Co-Authors

Nir Sochen
Nir Sochen Tel Aviv University
Alfred M. Bruckstein
Alfred M. Bruckstein Technion – Israel Institute of Technology
Ron Kimmel
Ron Kimmel Technion – Israel Institute of Technology
Yoav Y. Schechner
Yoav Y. Schechner Technion – Israel Institute of Technology
Hayit Greenspan
Hayit Greenspan Tel Aviv University
Dietmar Saupe
Dietmar Saupe University of Konstanz
Michael Lindenbaum
Michael Lindenbaum Technion – Israel Institute of Technology
Ronen Basri
Ronen Basri Weizmann Institute of Science
Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science
Tony F. Chan
Tony F. Chan University of California, Los Angeles

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