Image Analysis for Moving Organ, Breast, and Thoracic Images : Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings / edited by Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne Martel, Lena Maier-Hein, Kanwal Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga.

Format:

Book

Contributor:

Stoyanov, Danail, Editor.

Taylor, Zeike, Editor.

Kainz, Bernhard, Editor.

Maicas, Gabriel., Editor.

Beichel, Reinhard R., Editor.

Martel, Anne, Editor.

Maier-Hein, Lena., Editor.

Bhatia, Kanwal., Editor.

Vercauteren, Tom., Editor.

Oktay, Ozan., Editor.

Carneiro, Gustavo, Editor.

Bradley, Andrew P., Editor.

Nascimento, Jacinto., Editor.

Min, Hang., Editor.

Brown, Matthew S., Editor.

Jacobs, Colin., Editor.

Lassen-Schmidt, Bianca., Editor.

Mori, Kensaku, Editor.

Petersen, Jens, Editor.

San José Estépar, Raúl., Editor.

Schmidt-Richberg, Alexander, Editor.

Veiga, Catarina, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11040

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11040

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Medical informatics.

Computer networks.

Computer Vision.

Artificial Intelligence.

Health Informatics.

Computer Communication Networks.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Health Informatics.

Computer Communication Networks.

Physical Description:

1 online resource (XIV, 350 pages) : 144 illustrations

Edition:

1st ed. 2018.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2018.

System Details:

text file PDF

Summary:

This book constitutes the refereed joint proceedings of the Third International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2018, the Fourth International Workshop on Breast Image Analysis, BIA 2018, and the First International Workshop on Thoracic Image Analysis, TIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 5 full papers (out of 10 submissions) presented at RAMBO, the 9 full papers (out of 18 submissions) presented at BIA, and the 20 full papers (out of 21 submissions) presented at TIA were carefully reviewed and selected. The RAMBO papers cover aspects of medical imaging where motion plays a role in the image formation or analysis. The BIA papers deal with topics such as computer-aided detection and diagnosis of breast cancer, quantitative analysis of breast imaging modalities, and large scale breast image screening and analysis. The TIA papers cover aspects of image analysis research for lung and cardiac diseases including segmentation, registration, quantification, modeling of the image acquisition process, visualization, validation, statistical modeling, biophysical lung modeling (computational anatomy), deep learning and novel applications.

Contents:

Resection-based Demons Regularization for Breast Tumor Bed Propagation

Linear and Deformable Image Registration with 3D Convolutional Neural Networks

Super Resolution of Cardiac Cine MRI Sequences Using Deep Learning

Automated CNN-based Reconstruction of Short-Axis Cardiac MR Sequence From Real-Time Image Data

An Unbiased Groupwise Registration Algorithm for Correcting Motion in Dynamic Contrast-Enhanced Magnetic Resonance Images

Siamese Network for Dual-View Mammography Mass Matching

Large-scale Mammography CAD with Deformable Conv-Nets

Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images

Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net

Improving Breast Cancer Detection using Symmetry Information

Conditional Infilling GANs for Data Augmentation in Mammogram Classification

A Unified Mammogram Analysis Method via Hybrid Deep Supervision

Structure-aware Staging for Breast Cancer Metastases

Reproducible evaluation of registration algorithms for movement correction in dynamic contrast enhancing magnetic resonance imaging for breast cancer diagnosis

Robust Windowed Harmonic Phase Analysis with a Single Acquisition

Lung Structures Enhancement in Chest Radiographs via CT based FCNN Training

Improving the Segmentation of Anatomical Structures in Chest Radiographs using U-Net with an ImageNet Pre-trained Encoder

Tuberculosis histopathology on x-ray CT

A CT scan harmonization technique to detect Emphysema and Small Airway Diseases

Transfer Learning for Segmentation of Injured Lungs using Coarse-to-Fine Convolutional Neural Networks

High throughput lung and lobar segmentation by 2D and 3D CNN on chest CT with diffuse lung disease

Multi-Structure Segmentation from Partially Labeled Datasets. Application to Body Composition Measurements on CT scans

3D Pulmonary Artery Segmentation from CTA Scans using Deep Learning with Realistic Data Augmentation

Automatic Airway Segmentation in chest CT using Convolutional Neural Networks

Detecting Out-of-phase Ventilation Using 4DCT to Improve Radiation Therapy for Lung Cancer

XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-derived Motion Model

Rigid Lens - Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scan

Diffeomorphic Lung Registration using Deep CNNs and Reinforced Learning

Transfer learning approach to predict biopsy-confirmed malignancy of lung nodules from imaging data: a pilot study

Convolutional Neural Network Based COPD and Emphysema Classifications Are Predictive of Lung Cancer Diagnosis

Towards an automatic lung cancer screening system in low dose computed tomography

Automatic classification of centrilobular emphysema on CT using deep learning: comparison with visual scoring

On the Relevance of the Loss Function in the Agatston Score Regression from non-ECG Gated CT Scans

Accurate Measurement of Airway Morphology on Chest CT images.

Other Format:

Printed edition:

ISBN:

978-3-030-00946-5

9783030009465

Access Restriction:

Restricted for use by site license.