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Computer Science

D-Index
32
Citations
5961
World Ranking
12976
National Ranking
36

Overview

Martin Urschler is affiliated with the University of Auckland in New Zealand. Their research spans multiple disciplines including medicine, computer science, and engineering.

The main fields of study in Urschler's work include:

  • Medicine
  • Computer Science
  • Engineering

Within these fields, Urschler has contributed to several subfields, notably:

  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering
  • Oral Surgery
  • Artificial Intelligence

Their research covers key topics such as:

  • Dental Radiography and Imaging
  • Medical Imaging and Analysis
  • Forensic Anthropology and Bioarchaeology Studies
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Medical Image Segmentation Techniques
  • Advanced X-ray and CT Imaging

Urschler has published in several academic venues, including:

  • arXiv (Cornell University)
  • TUGraz OPEN Library (Graz University of Technology)
  • Medical Image Analysis
  • Journal of Food Measurement & Characterization
  • Bioengineering

Among recent papers authored or coauthored by Urschler are:

  • VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images, 2021, Medical Image Analysis
  • A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs, 2021, Medical Image Analysis
  • Generative Adversarial Network based Synthesis for Supervised Medical Image Segmentation, 2020, TUGraz OPEN Library (Graz University of Technology)
  • Wavelength and texture feature selection for hyperspectral imaging: a systematic literature review, 2023, Journal of Food Measurement & Characterization
  • Automated pneumothorax triaging in chest X-rays in the New Zealand population using deep-learning algorithms, 2022, Journal of Medical Imaging and Radiation Oncology

Frequent coauthors in Urschler's body of work include:

  • Darko Štern
  • Christian Payer
  • Franz Thaler
  • Gernot Plank
  • Matthias A. F. Gsell

Best Publications

  • Gland segmentation in colon histology images: The GlaS challenge contest

    Korsuk Sirinukunwattana;Josien P.W. Pluim;Hao Chen;Xiaojuan Qi

  • Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

    K. Murphy;B. van Ginneken;J. M. Reinhardt;S. Kabus

  • Integrating spatial configuration into heatmap regression based CNNs for landmark localization.

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

    Xiahai Zhuang;Lei Li;Christian Payer;Darko Stern

  • VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

    Anjany Sekuboyina;Malek E. Husseini;Amirhossein Bayat;Maximilian Löffler

  • Saliency driven total variation segmentation

    Michael Donoser;Martin Urschler;Martin Hirzer;Horst Bischof

  • Regressing Heatmaps for Multiple Landmark Localization Using CNNs

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

    Rina D. Rudyanto;Sjoerd Kerkstra;Eva M. van Rikxoort;Catalin Fetita

  • A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs.

    Karli Gillette;Matthias A.F. Gsell;Anton J. Prassl;Elias Karabelas;Elias Karabelas

  • Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations

    Christian Payer;Darko Štern;Horst Bischof;Martin Urschler

  • A duality based algorithm for TV-L¹-optical-flow image registration

    Thomas Pock;Martin Urschler;Christopher Zach;Reinhard Beichel

  • A multi-center milestone study of clinical vertebral CT segmentation

    Jianhua Yao;Joseph E. Burns;Daniel Forsberg;Alexander Seitel

  • Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

    Philipp Kainz;Philipp Kainz;Michael Pfeiffer;Martin Urschler

  • You Should Use Regression to Detect Cells

    Philipp Kainz;Martin Urschler;Samuel Schulter;Paul Wohlhart

  • Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net.

    Christian Payer;Darko Stern;Horst Bischof;Martin Urschler

  • Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networks

    Christian Payer;Darko Štern;Thomas Neff;Horst Bischof

  • Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge.

    Guoyan Zheng;Chengwen Chu;Daniel L. Belavý;Daniel L. Belavý;Bulat Ibragimov

  • Integrating geometric configuration and appearance information into a unified framework for anatomical landmark localization

    Martin Urschler;Thomas Ebner;Darko Štern

  • Towards Automatic Bone Age Estimation from MRI: Localization of 3D Anatomical Landmarks

    Thomas Ebner;Darko Stern;Rene Donner;Horst Bischof

  • Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data

    Darko Stern;Christian Payer;Nicola Giuliani;Martin Urschler

  • SIFT and shape context for feature-based nonlinear registration of thoracic CT images

    Martin Urschler;Joachim Bauer;Hendrik Ditt;Horst Bischof

  • Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net

    Christian Payer;Darko Stern;Horst Bischof;Martin Urschler

Frequent Co-Authors

Horst Bischof
Horst Bischof Graz University of Technology
Thomas Pock
Thomas Pock Graz University of Technology
Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong
Michael Pfeiffer
Michael Pfeiffer Bosch Center for Artificial Intelligence
Sebastien Ourselin
Sebastien Ourselin King's College London
Ben Glocker
Ben Glocker Imperial College London
Josien P. W. Pluim
Josien P. W. Pluim Eindhoven University of Technology
Guoyan Zheng
Guoyan Zheng Shanghai Jiao Tong University
Mattias P. Heinrich
Mattias P. Heinrich University of Lübeck
Dieter Schmalstieg
Dieter Schmalstieg University of Stuttgart

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