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

Zhou, Zongwei (et al.)

Seiten 3-11

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Deep Semi-supervised Segmentation with Weight-Averaged Consistency Targets

Perone, Christian S. (et al.)

Seiten 12-19

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Handling Missing Annotations for Semantic Segmentation with Deep ConvNets

Petit, Olivier (et al.)

Seiten 20-28

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

Jafari, Mohammad H. (et al.)

Seiten 29-37

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

Peng, Liying (et al.)

Seiten 38-46

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

Zhao, Mengliu (et al.)

Seiten 47-55

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

He, Zhou (et al.)

Seiten 56-64

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

Behnami, Delaram (et al.)

Seiten 65-73

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

Liu, Lihao (et al.)

Seiten 74-82

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

Sourati, Jamshid (et al.)

Seiten 83-91

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Contextual Additive Networks to Efficiently Boost 3D Image Segmentations

Xu, Zhenlin (et al.)

Seiten 92-100

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Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration

Krebs, Julian (et al.)

Seiten 101-109

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

Reid, Lee B. (et al.)

Seiten 110-118

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Focal Dice Loss and Image Dilation for Brain Tumor Segmentation

Wang, Pei (et al.)

Seiten 119-127

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

Spilger, Roman (et al.)

Seiten 128-136

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3D Convolutional Neural Networks for Classification of Functional Connectomes

Khosla, Meenakshi (et al.)

Seiten 137-145

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

Vandewinckele, Liesbeth (et al.)

Seiten 146-154

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Unpaired Deep Cross-Modality Synthesis with Fast Training

Xiang, Lei (et al.)

Seiten 155-164

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UOLO - Automatic Object Detection and Segmentation in Biomedical Images

Araújo, Teresa (et al.)

Seiten 165-173

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

Yang, Heran (et al.)

Seiten 174-182

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Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy

Ozdemir, Firat (et al.)

Seiten 183-191

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Weakly Supervised Localisation for Fetal Ultrasound Images

Toussaint, Nicolas (et al.)

Seiten 192-200

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PIMMS: Permutation Invariant Multi-modal Segmentation

Varsavsky, Thomas (et al.)

Seiten 201-209

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

Alaverdyan, Zara (et al.)

Seiten 210-217

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

Lamash, Yechiel (et al.)

Seiten 218-226

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

Kumar, Shubham (et al.)

Seiten 227-235

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Learning to Segment Medical Images with Scribble-Supervision Alone

Can, Yigit B. (et al.)

Seiten 236-244

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

Sharma, Aditya (et al.)

Seiten 245-253

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

Etcheverry, Mayalen (et al.)

Seiten 254-262

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

Dai, Wei (et al.)

Seiten 263-273

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

Combalia, Marc (et al.)

Seiten 274-281

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

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

Seiten 282-290

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

Li, Meng (et al.)

Seiten 291-299

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Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks

Iglovikov, Vladimir I. (et al.)

Seiten 300-308

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Automatic Myocardial Strain Imaging in Echocardiography Using Deep Learning

Østvik, Andreas (et al.)

Seiten 309-316

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

Dong, Nanqing (et al.)

Seiten 317-325

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Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM

Santeramo, Ruggiero (et al.)

Seiten 326-333

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

Pace, Danielle F. (et al.)

Seiten 334-342

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

Lau, Felix (et al.)

Seiten 343-350

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

Cheng, Myra (et al.)

Seiten 353-360

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

Lei, Haijun (et al.)

Seiten 361-368

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

Sadhukhan, Sandip (et al.)

Seiten 369-376

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Integrating Deformable Modeling with 3D Deep Neural Network Segmentation

Tang, Hui (et al.)

Seiten 377-384

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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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