Image Processing, Computer Vision, Pattern Recognition, and Graphics

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

Herausgeber: Stoyanov, D., Taylor, Z., Carneiro, G., Syeda-Mahmood, T., Martel, A., Maier-Hein, L., Tavares, J.M.R.S., Bradley, A., Papa, J.P., Belagiannis, V., Nascimento, J.C., Lu, Z., Conjeti, S., Moradi, M., Greenspan, H., Madabhushi, A. (Eds.)

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Über dieses Buch: This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 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 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

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Inhaltsverzeichnis (43 Kapitel)

Inhaltsverzeichnis (43 Kapitel)

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

Seiten 3-11

Zhou, Zongwei (et al.)

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Deep Semi-supervised Segmentation with Weight-Averaged Consistency Targets

Seiten 12-19

Perone, Christian S. (et al.)

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Handling Missing Annotations for Semantic Segmentation with Deep ConvNets

Seiten 20-28

Petit, Olivier (et al.)

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A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data

Seiten 29-37

Jafari, Mohammad H. (et al.)

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Multi-scale Residual Network with Two Channels of Raw CT Image and Its Differential Excitation Component for Emphysema Classification

Seiten 38-46

Peng, Liying (et al.)

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TreeNet: Multi-loss Deep Learning Network to Predict Branch Direction for Extracting 3D Anatomical Trees

Seiten 47-55

Zhao, Mengliu (et al.)

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3D Deep Affine-Invariant Shape Learning for Brain MR Image Segmentation

Seiten 56-64

He, Zhou (et al.)

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Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography

Seiten 65-73

Behnami, Delaram (et al.)

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MTMR-Net: Multi-task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis

Seiten 74-82

Liu, Lihao (et al.)

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Active Deep Learning with Fisher Information for Patch-Wise Semantic Segmentation

Seiten 83-91

Sourati, Jamshid (et al.)

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Contextual Additive Networks to Efficiently Boost 3D Image Segmentations

Seiten 92-100

Xu, Zhenlin (et al.)

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Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration

Seiten 101-109

Krebs, Julian (et al.)

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Rapid Training Data Generation for Tissue Segmentation Using Global Approximate Block-Matching with Self-organizing Maps

Seiten 110-118

Reid, Lee B. (et al.)

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Focal Dice Loss and Image Dilation for Brain Tumor Segmentation

Seiten 119-127

Wang, Pei (et al.)

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Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning

Seiten 128-136

Spilger, Roman (et al.)

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3D Convolutional Neural Networks for Classification of Functional Connectomes

Seiten 137-145

Khosla, Meenakshi (et al.)

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Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks

Seiten 146-154

Vandewinckele, Liesbeth (et al.)

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Unpaired Deep Cross-Modality Synthesis with Fast Training

Seiten 155-164

Xiang, Lei (et al.)

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UOLO - Automatic Object Detection and Segmentation in Biomedical Images

Seiten 165-173

Araújo, Teresa (et al.)

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Unpaired Brain MR-to-CT Synthesis Using a Structure-Constrained CycleGAN

Seiten 174-182

Yang, Heran (et al.)

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Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy

Seiten 183-191

Ozdemir, Firat (et al.)

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Weakly Supervised Localisation for Fetal Ultrasound Images

Seiten 192-200

Toussaint, Nicolas (et al.)

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PIMMS: Permutation Invariant Multi-modal Segmentation

Seiten 201-209

Varsavsky, Thomas (et al.)

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Unsupervised Feature Learning for Outlier Detection with Stacked Convolutional Autoencoders, Siamese Networks and Wasserstein Autoencoders: Application to Epilepsy Detection

Seiten 210-217

Alaverdyan, Zara (et al.)

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Semi-automated Extraction of Crohns Disease MR Imaging Markers Using a 3D Residual CNN with Distance Prior

Seiten 218-226

Lamash, Yechiel (et al.)

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Learning Optimal Deep Projection of $$^{18}$$F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes

Seiten 227-235

Kumar, Shubham (et al.)

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Learning to Segment Medical Images with Scribble-Supervision Alone

Seiten 236-244

Can, Yigit B. (et al.)

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Learning to Decode 7T-Like MR Image Reconstruction from 3T MR Images

Seiten 245-253

Sharma, Aditya (et al.)

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Nonlinear Adaptively Learned Optimization for Object Localization in 3D Medical Images

Seiten 254-262

Etcheverry, Mayalen (et al.)

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SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays

Seiten 263-273

Dai, Wei (et al.)

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Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification

Seiten 274-281

Combalia, Marc (et al.)

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Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network

Seiten 282-290

Imran, Abdullah-Al-Zubaer (et al.)

Vorschau Kapitel kaufen 29,69 €
Computed Tomography Image Enhancement Using 3D Convolutional Neural Network

Seiten 291-299

Li, Meng (et al.)

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Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks

Seiten 300-308

Iglovikov, Vladimir I. (et al.)

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Automatic Myocardial Strain Imaging in Echocardiography Using Deep Learning

Seiten 309-316

Østvik, Andreas (et al.)

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Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images

Seiten 317-325

Dong, Nanqing (et al.)

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Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM

Seiten 326-333

Santeramo, Ruggiero (et al.)

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Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease

Seiten 334-342

Pace, Danielle F. (et al.)

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ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans

Seiten 343-350

Lau, Felix (et al.)

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A Multi-scale Multiple Sclerosis Lesion Change Detection in a Multi-sequence MRI

Seiten 353-360

Cheng, Myra (et al.)

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Multi-task Sparse Low-Rank Learning for Multi-classification of Parkinson’s Disease

Seiten 361-368

Lei, Haijun (et al.)

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Optic Disc Segmentation in Retinal Fundus Images Using Fully Convolutional Network and Removal of False-Positives Based on Shape Features

Seiten 369-376

Sadhukhan, Sandip (et al.)

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Integrating Deformable Modeling with 3D Deep Neural Network Segmentation

Seiten 377-384

Tang, Hui (et al.)

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Buchtitel

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Buchuntertitel

4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

Herausgeber

Danail Stoyanov
Zeike Taylor
Gustavo Carneiro
Tanveer Syeda-Mahmood
Anne Martel
Lena Maier-Hein
João Manuel R. S. Tavares
Andrew Bradley
Joao Paulo Papa
Vasileios Belagiannis
Jacinto C. Nascimento
Zhi Lu
Sailesh Conjeti
Mehdi Moradi
Hayit Greenspan
Anant Madabhushi

Titel der Buchreihe

Image Processing, Computer Vision, Pattern Recognition, and Graphics

Buchreihen Band

11045

Copyright

2018

Verlag

Springer International Publishing

Copyright Inhaber

Springer Nature Switzerland AG

eBook ISBN: 978-3-030-00889-5
DOI: 10.1007/978-3-030-00889-5
Softcover ISBN: 978-3-030-00888-8
Auflage: 1

Seitenzahl

XVII, 387

Anzahl der Bilder

159 schwarz-weiß Abbildungen

Themen

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