Anatomy Detection and Localization in 3D Medical Images

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Unknown venue

• Publication date

  Unknown publication date

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1007/978-1-4471-4929-3_14
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

  2012cited by this paper
• Automatic Localization and Identification of Vertebrae in Arbitrary Field-of-View CT Scans

  2012cited by this paper
• Fast Multiple Organ Detection and Localization in Whole-Body MR Dixon Sequences

  2011cited by this paper
• Robust linear registration of CT images using random regression forests

  2011cited by this paper
• Automatic Semantic Annotation and Validation of Anatomy in DICOM CT Images

  2011cited by this paper
• Regression Forests for Efficient Anatomy Detection and Localization in CT Studies

  2010cited by this paper
• elastix: A Toolbox for Intensity-Based Medical Image Registration

  2010cited by this paper
• Decision Forests with Long-Range Spatial Context for Organ Localization in CT Volumes

  2009cited by this paper
• Hierarchical parsing and semantic navigation of full body CT data

  2009cited by this paper
• Estimating the body portion of CT volumes by matching histograms of visual words

  2009cited by this paper
• Multi-Atlas-Based Segmentation With Local Decision Fusion—Application to Cardiac and Aortic Segmentation in CT Scans

  2009cited by this paper
• Class-specific Hough forests for object detection

  2009cited by this paper
• Active Scheduling of Organ Detection and Segmentation in Whole-Body Medical Images

  2008cited by this paper
• Dixon techniques for water and fat imaging

  2008cited by this paper
• Automatic Labeling of Anatomical Structures in MR FastView Images Using a Statistical Atlas

  2008cited by this paper
• A boosting regression approach to medical anatomy detection

  2007cited by this paper
• TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

  2007cited by this paper
• Sharing Visual Features for Multiclass and Multiview Object Detection

  2007cited by this paper
• Tree-based Classifiers for Bilayer Video Segmentation

  2007cited by this paper
• Multi-organ segmentation in three dimensional abdominal CT images

  2006cited by this paper
• Image based regression using boosting method

  2005cited by this paper
• Simultaneous segmentation of multi-organ in three dimensional abdominal CT images

  2005cited by this paper
• Quality of DICOM header information for image categorization

  2002cited by this paper
• Robust Real-Time Face Detection

  2001cited by this paper
• Greedy function approximation: A gradient boosting machine.

  2001cited by this paper
• The Nature of Statistical Learning Theory

  2000cited by this paper
• Medical Image Computing and Computer-Assisted Intervention — MICCAI’98

  1998cited by this paper
• A comparative study of texture measures with classification based on featured distributions

  1996cited by this paper
• Storage and Retrieval for Image and Video Databases

  1993cited by this paper
• A Simplex Method for Function Minimization

  1965cited by this paper

• Automatic Detection of Anatomical Regions in Three-Dimensional Medical Images

  2021cites this paper
• Automatische Detektion von Zwischenorgan-3D-Barrieren in abdominalen CT-Daten

  2020influential citation
• Prediction of ocean import shipment lead time using machine learning methods

  2020cites this paper
• Automatic multi-object organ detection and segmentation in abdominal CT data

  2020cites this paper
• Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

  2019cites this paper
• International Journal of Recent Technology and Engineering (IJRTE)

  2019cites this paper
• Organ Segmentation in Poultry Viscera Using RGB-D

  2018cites this paper
• Computer Vision Analysis of Broiler Carcass and Viscera

  2018cites this paper
• Aalborg Universitet Organ Segmentation in Poultry Viscera Using RGB -

  2018cites this paper
• Light Random Regression Forests for automatic multi-organ localization in CT images

  2017influential citation
• Random Forests for Localization of Spinal Anatomy

  2016cites this paper
• Automatic recognition of anatomical regions in three-dimensional medical images

  2016cites this paper
• Learning clinically useful information from images: Past, present and future

  2016cites this paper
• Fast Automatic Vertebrae Detection and Localization in Pathological CT Scans - A Deep Learning Approach

  2015cites this paper
• Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

  2015cites this paper
• Cervical vertebral corner detection using haar-like features and modified hough forest

  2015cites this paper
• Machine Learning and Knowledge Extraction in Digital Pathology Needs an Integrative Approach

  2015cites this paper
• Automatic vertebrae localization, identification, and segmentation using deep learning and statistical models

  2014cites this paper
• Organ detection in medical images with discriminately trained deformable part model

  2013cites this paper