Computational Methods and Clinical Applications in Musculoskeletal Imaging 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers

Computational Methods and Clinical Applications in Musculoskeletal Imaging 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers / edited by Ben Glocker, Jianhua Yao, Tomaž Vrtovec, Alejandro Frangi, Guoyan Zheng.

This book constitutes the refereed proceedings of the 5th International Workshop and Challenge on Computational Methods and Clinical Applications for Musculoskeletal Imaging, MSKI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 13 workshop papers were c...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Glocker, Ben (Editor), Yao, Jianhua (Editor), Vrtovec, Tomaž (Editor), Frangi, Alejandro (Editor), Zheng, Guoyan (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Computer Communication Networks and Telecommunications ; 10734
Springer eBook Collection.
Subjects:
Optical data processing.
Artificial intelligence.
Computer communication systems.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps
  • Shape-aware Deep Convolutional Neural Network for Vertebrae Segmentation
  • Automated Characterization of Body Composition and Frailty with Clinically Acquired CT
  • Unfolded cylindrical projection for rib fracture diagnosis
  • 3D Cobb Angle Measurements from Scoliotic Mesh Models with Varying Face-Vertex Density
  • Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features
  • Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients
  • Reconstruction of 3D muscle fiber structure using high resolution cryosectioned volume
  • Segmentation of Pathological Spines in CT Images Using a Two-Way CNN and a Collision-Based Model
  • Attention-driven deep learning for pathological spine segmentation
  • Automatic Full Femur Segmentation from Computed Tomography Datasets using an Atlas-Based Approach
  • Classification of Osteoporotic Vertebral Fractures using Shape and Appearance Modelling
  • DSMS-FCN: A Deeply Supervised Multi-Scale Fully Convolutional Network for Automatic Segmentation of Intervertebral Disc in 3D MR Images.

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