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E-grāmata: Medical Computer Vision: Algorithms for Big Data: International Workshop, MCV 2014, Held in Conjunction with MICCAI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers

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This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in conjunction with the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014. The one-day workshop aimed at exploring the use of modern computer vision technology and "big data" algorithms in tasks such as automatic segmentation and registration, localization of anatomical features and detection of anomalies emphasizing questions of harvesting, organizing and learning from large-scale medical imaging data sets and general-purpose automatic understanding of medical images. The 18 full and 1 short papers presented in this volume were carefully reviewed and selected from 30 submission.
Workshop Overview
Overview of the 2014 Workshop on Medical Computer Vision---Algorithms for Big Data (MCV 2014)
3(10)
Henning Muller
Bjoern Menze
Georg Langs
Albert Montillo
Michael Kelm
Shooting Zhang
Weidong (Tom) Cai
Dimitris Metaxas
Segmentation of Big Medical Data
Joint Segmentation and Registration for Infant Brain Images
13(9)
Guorong Wu
Li Wang
John Gilmore
Weili Lin
Dinggang Shen
LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images
22(12)
Li Wang
Yaozong Gao
Feng Shi
Gang Li
John H. Gilmore
Weili Lin
Dinggang Shen
Pectoralis Muscle Segmentation on CT Images Based on Bayesian Graph Cuts with a Subject-Tailored Atlas
34(13)
Rola Harmouche
James C. Ross
George R. Washko
Raul San Jose Estepar
Advanced Feature Extraction
Learning Features for Tissue Classification with the Classification Restricted Boltzmann Machine
47(12)
Gijs van Tulder
Marleen de Bruijne
Dementia-Related Features in Longitudinal MRI: Tracking Keypoints over Time
59(12)
Elisabeth Stuhler
Michael R. Berthold
Object Classification in an Ultrasound Video Using LP-SIFT Features
71(11)
Mohammad Ali Maraci
Raffaele Napolitano
Aris Papageorghiou
J. Allison Noble
Unsupervised Pre-training Across Image Domains Improves Lung Tissue Classification
82(15)
Thomas Schlegl
Joachim Ofner
Georg Langs
Multi-atlas and Beyond
Atlas-Guided Multi-channel Forest Learning for Human Brain Labeling
97(8)
Guangkai Ma
Yaozong Gao
Guorong Wu
Ligang Wu
Dinggang Shen
Fast Multiatlas Selection Using Composition of Transformations for Radiation Therapy Planning
105(11)
David Rivest-Henault
Soumya Ghose
Josien P. W. Pluim
Peter B. Greer
Jurgen Fripp
Jason A. Dowling
Classifier-Based Multi-atlas Label Propagation with Test-Specific Atlas Weighting for Correspondence-Free Scenarios
116(11)
Darko Zikic
Ben Glocker
Antonio Criminisi
Translational Medical Computer Vision
CT Prostate Deformable Segmentation by Boundary Regression
127(10)
Yeqin Shao
Yaozong Gao
Xin Yang
Dinggang Shen
Precise Lumen Segmentation in Coronary Computed Tomography Angiography
137(11)
Felix Lugauer
Yefeng Zheng
Joachim Hornegger
B. Michael Kelm
Confidence-Based Training for Clinical Data Uncertainty in Image-Based Prediction of Cardiac Ablation Targets
148(15)
Rocio Cabrera-Lozoya
Jan Margeta
Loic Le Folgoc
Yuki Komatsu
Benjamin Berte
Jatin Relan
Hubert Cochet
Michel Haissaguerre
Pierre Jais
Nicholas Ayache
Maxime Sermesant
VISCERAL Session
Rule-Based Ventral Cavity Multi-organ Automatic Segmentation in CT Scans
163(8)
Assaf B. Spanier
Leo Joskowicz
Multi-atlas Segmentation and Landmark Localization in Images with Large Field of View
171(10)
Tobias Gass
Gabor Szekely
Orcun Goksel
Automatic Liver Segmentation Using Statistical Prior Models and Free-form Deformation
181
Xuhui Li
Cheng Huang
Fucang Jia
Zongmin Li
Chihua Fang
Yingfang Fan