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Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 : 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part I

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Cover of 'Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 : 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part I'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Leveraging Random Forests for Interactive Exploration of Large Histological Images
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    Chapter 2 Cell Detection and Segmentation Using Correlation Clustering
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    Chapter 3 Candidate Sampling for Neuron Reconstruction from Anisotropic Electron Microscopy Volumes
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    Chapter 4 A Fully Bayesian Inference Framework for Population Studies of the Brain Microstructure
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    Chapter 5 Shading Correction for Whole Slide Image Using Low Rank and Sparse Decomposition
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    Chapter 6 Cell-Sensitive Microscopy Imaging for Cell Image Segmentation
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    Chapter 7 A Probabilistic Approach to Quantification of Melanin and Hemoglobin Content in Dermoscopy Images
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    Chapter 8 Automated, Non-Invasive Characterization of Stem Cell-Derived Cardiomyocytes from Phase-Contrast Microscopy
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    Chapter 9 Exploiting Enclosing Membranes and Contextual Cues for Mitochondria Segmentation
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    Chapter 10 Identifying Neutrophils in H&E Staining Histology Tissue Images
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    Chapter 11 Active Graph Matching for Automatic Joint Segmentation and Annotation of C. elegans
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    Chapter 12 Semi-automated Query Construction for Content-Based Endomicroscopy Video Retrieval
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    Chapter 13 Optree: A Learning-Based Adaptive Watershed Algorithm for Neuron Segmentation
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    Chapter 14 Application-Driven MRI: Joint Reconstruction and Segmentation from Undersampled MRI Data
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    Chapter 15 Joint Parametric Reconstruction and Motion Correction Framework for Dynamic PET Data
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    Chapter 16 Deformable Reconstruction of Histology Sections Using Structural Probability Maps
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    Chapter 17 Optimally Stabilized PET Image Denoising Using Trilateral Filtering
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    Chapter 18 Real Time Dynamic MRI with Dynamic Total Variation
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    Chapter 19 Improved Reconstruction of 4D-MR Images by Motion Predictions
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    Chapter 20 Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion
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    Chapter 21 Speckle reduction in optical coherence tomography by image registration and matrix completion.
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    Chapter 22 Signal Decomposition for X-ray Dark-Field Imaging
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    Chapter 23 Iterative Most Likely Oriented Point Registration
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    Chapter 24 Robust Anatomical Landmark Detection for MR Brain Image Registration
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    Chapter 25 Free-Form Deformation Using Lower-Order B-spline for Nonrigid Image Registration
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    Chapter 26 Multispectral Image Registration Based on Local Canonical Correlation Analysis
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    Chapter 27 Topology Preservation and Anatomical Feasibility in Random Walker Image Registration
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    Chapter 28 DR-BUDDI: Diffeomorphic Registration for Blip Up-Down Diffusion Imaging
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    Chapter 29 Spatially-Varying Metric Learning for Diffeomorphic Image Registration: A Variational Framework
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    Chapter 30 Sparse Bayesian Registration
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    Chapter 31 Histology to μCT Data Matching Using Landmarks and a Density Biased RANSAC
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    Chapter 32 Robust Registration of Longitudinal Spine CT
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    Chapter 33 Geometric-Feature-Based Spectral Graph Matching in Pharyngeal Surface Registration
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    Chapter 34 Gaussian Process Interpolation for Uncertainty Estimation in Image Registration
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    Chapter 35 Hough Space Parametrization: Ensuring Global Consistency in Intensity-Based Registration
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    Chapter 36 2D/3D Registration of TEE Probe from Two Non-orthogonal C-Arm Directions
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    Chapter 37 Reduced-Dose Patient to Baseline CT Rigid Registration in 3D Radon Space
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    Chapter 38 Hierarchical Label Fusion with Multiscale Feature Representation and Label-Specific Patch Partition
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    Chapter 39 Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature
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    Chapter 40 Atlas-Based Under-Segmentation
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    Chapter 41 Bayesian Model Selection for Pathological Data
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    Chapter 42 Automatic Localization of Cochlear Implant Electrodes in CT
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    Chapter 43 Coronary Lumen and Plaque Segmentation from CTA Using Higher-Order Shape Prior
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    Chapter 44 Multi-atlas Spectral PatchMatch: Application to Cardiac Image Segmentation
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    Chapter 45 Robust Bone Detection in Ultrasound Using Combined Strain Imaging and Envelope Signal Power Detection
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    Chapter 46 SIMPLE Is a Good Idea (and Better with Context Learning)
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    Chapter 47 Segmentation of Multiple Knee Bones from CT for Orthopedic Knee Surgery Planning
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    Chapter 48 TRIC: Trust Region for Invariant Compactness and Its Application to Abdominal Aorta Segmentation
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    Chapter 49 Small Sample Learning of Superpixel Classifiers for EM Segmentation
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    Chapter 50 A Cautionary Analysis of STAPLE Using Direct Inference of Segmentation Truth
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    Chapter 51 Auto Localization and Segmentation of Occluded Vessels in Robot-Assisted Partial Nephrectomy
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    Chapter 52 3D Global Estimation and Augmented Reality Visualization of Intra-operative X-ray Dose
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    Chapter 53 Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
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    Chapter 54 Pico Lantern: A Pick-up Projector for Augmented Reality in Laparoscopic Surgery
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    Chapter 55 Efficient Stereo Image Geometrical Reconstruction at Arbitrary Camera Settings from a Single Calibration
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    Chapter 56 A Compact Active Stereovision System with Dynamic Reconfiguration for Endoscopy or Colonoscopy Applications
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    Chapter 57 Continuous Zoom Calibration by Tracking Salient Points in Endoscopic Video
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    Chapter 58 Instrument Tracking via Online Learning in Retinal Microsurgery
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    Chapter 59 Estimating a Patient Surface Model for Optimizing the Medical Scanning Workflow
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    Chapter 60 3D Steering of a Flexible Needle by Visual Servoing
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    Chapter 61 Improved Screw Placement for Slipped Capital Femoral Epiphysis (SCFE) Using Robotically-Assisted Drill Guidance
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    Chapter 62 Hierarchical HMM Based Learning of Navigation Primitives for Cooperative Robotic Endovascular Catheterization
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    Chapter 63 Towards Personalized Interventional SPECT-CT Imaging
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    Chapter 64 Chest Modeling and Personalized Surgical Planning for Pectus Excavatum
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    Chapter 65 A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations
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    Chapter 66 Towards Automatic Plan Selection for Radiotherapy of Cervical Cancer by Fast Automatic Segmentation of Cone Beam CT Scans
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    Chapter 67 Breast Cancer Risk Analysis Based on a Novel Segmentation Framework for Digital Mammograms
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    Chapter 68 2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers
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    Chapter 69 Patient Specific Image Driven Evaluation of the Aggressiveness of Metastases to the Lung
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    Chapter 70 Multi-parametric 3D Quantitative Ultrasound Vibro-Elastography Imaging for Detecting Palpable Prostate Tumors
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    Chapter 71 Multi-stage Thresholded Region Classification for Whole-Body PET-CT Lymphoma Studies
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    Chapter 72 fhSPECT-US Guided Needle Biopsy of Sentinel Lymph Nodes in the Axilla: Is it Feasible?
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    Chapter 73 Gland Ring Morphometry for Prostate Cancer Prognosis in Multispectral Immunofluorescence Images
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    Chapter 74 Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model
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    Chapter 75 Bone Tumor Segmentation on Bone Scans Using Context Information and Random Forests
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    Chapter 76 Automated Colorectal Tumour Segmentation in DCE-MRI Using Supervoxel Neighbourhood Contrast Characteristics
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    Chapter 77 Real-Time Visualisation and Analysis of Internal Examinations – Seeing the Unseen
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    Chapter 78 Tracing Retinal Blood Vessels by Matrix-Forest Theorem of Directed Graphs
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    Chapter 79 Learning Fully-Connected CRFs for Blood Vessel Segmentation in Retinal Images
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    Chapter 80 Feature Space Optimization for Virtual Chromoendoscopy Augmented by Topography
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    Chapter 81 Multi-frame Super-resolution with Quality Self-assessment for Retinal Fundus Videos
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    Chapter 82 An Automated System for Detecting and Measuring Nailfold Capillaries
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    Chapter 83 Geodesic Patch-Based Segmentation
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    Chapter 84 Tagged Template Deformation
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    Chapter 85 Segmentation of the Right Ventricle Using Diffusion Maps and Markov Random Fields
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    Chapter 86 Differential and Relaxed Image Foresting Transform for Graph-Cut Segmentation of Multiple 3D Objects
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    Chapter 87 Segmentation Based Denoising of PET Images: An Iterative Approach via Regional Means and Affinity Propagation
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    Chapter 88 Detection and Registration of Ribs in MRI Using Geometric and Appearance Models
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    Chapter 89 Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation
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    Chapter 90 Robust Cortical Thickness Measurement with LOGISMOS-B
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    Chapter 91 Label Inference with Registration and Patch Priors
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    Chapter 92 Automated 3D Segmentation of Multiple Surfaces with a Shared Hole: Segmentation of the Neural Canal Opening in SD-OCT Volumes
  94. Altmetric Badge
    Chapter 93 Coupled Sparse Dictionary for Depth-Based Cup Segmentation from Single Color Fundus Image
  95. Altmetric Badge
    Chapter 94 Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
  96. Altmetric Badge
    Chapter 95 Combining Generative Models for Multifocal Glioma Segmentation and Registration
  97. Altmetric Badge
    Chapter 96 Partial Volume Estimation in Brain MRI Revisited
  98. Altmetric Badge
    Chapter 97 Sparse Appearance Learning Based Automatic Coronary Sinus Segmentation in CTA
  99. Altmetric Badge
    Chapter 98 Optic Cup Segmentation for Glaucoma Detection Using Low-Rank Superpixel Representation
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    Chapter 99 Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
  101. Altmetric Badge
    Chapter 100 Lung Segmentation from CT with Severe Pathologies Using Anatomical Constraints
  102. Altmetric Badge
    Chapter 101 Erratum: Iterative Most Likely Oriented Point Registration
Attention for Chapter 65: A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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2 patents


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Chapter title
A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations
Chapter number 65
Book title
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Published in
Lecture notes in computer science, September 2014
DOI 10.1007/978-3-319-10404-1_65
Pubmed ID
Book ISBNs
978-3-31-910403-4, 978-3-31-910404-1

Holger R. Roth, Le Lu, Ari Seff, Kevin M. Cherry, Joanne Hoffman, Shijun Wang, Jiamin Liu, Evrim Turkbey, Ronald M. Summers, Roth, Holger R., Lu, Le, Seff, Ari, Cherry, Kevin M., Hoffman, Joanne, Wang, Shijun, Liu, Jiamin, Turkbey, Evrim, Summers, Ronald M.


Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely distributed locations. State-of-the-art studies show the performance range of 52.9% sensitivity at 3.1 false-positives per volume (FP/vol.), or 60.9% at 6.1 FP/vol. for mediastinal LN, by one-shot boosting on 3D HAAR features. In this paper, we first operate a preliminary candidate generation stage, towards -100% sensitivity at the cost of high FP levels (-40 per patient), to harvest volumes of interest (VOI). Our 2.5D approach consequently decomposes any 3D VOI by resampling 2D reformatted orthogonal views N times, via scale, random translations, and rotations with respect to the VOI centroid coordinates. These random views are then used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign LN probabilities for all N random views that can be simply averaged (as a set) to compute the final classification probability per VOI. We validate the approach on two datasets: 90 CT volumes with 388 mediastinal LNs and 86 patients with 595 abdominal LNs. We achieve sensitivities of 70%/83% at 3 FP/vol. and 84%/90% at 6 FP/vol. in mediastinum and abdomen respectively, which drastically improves over the previous state-of-the-art work.

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The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 364 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Norway 1 <1%
India 1 <1%
Colombia 1 <1%
Canada 1 <1%
United Kingdom 1 <1%
Japan 1 <1%
China 1 <1%
Unknown 355 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 82 23%
Researcher 62 17%
Student > Master 61 17%
Student > Bachelor 24 7%
Student > Doctoral Student 17 5%
Other 49 13%
Unknown 69 19%
Readers by discipline Count As %
Computer Science 132 36%
Engineering 67 18%
Medicine and Dentistry 31 9%
Agricultural and Biological Sciences 9 2%
Physics and Astronomy 8 2%
Other 26 7%
Unknown 91 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 April 2023.
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