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ORCIDDLMIA/ML-CDS@MICCAI 2018: Granada, Spain
- Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, Anne L. Martel, Lena Maier-Hein, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, Anant Madabhushi:
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. Lecture Notes in Computer Science 11045, Springer 2018, ISBN 978-3-030-00888-8
4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018
- Zongwei Zhou
, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang:
UNet++: A Nested U-Net Architecture for Medical Image Segmentation. 3-11 - Christian S. Perone, Julien Cohen-Adad:
Deep Semi-supervised Segmentation with Weight-Averaged Consistency Targets. 12-19 - Olivier Petit, Nicolas Thome, Arnaud Charnoz, Alexandre Hostettler, Luc Soler:
Handling Missing Annotations for Semantic Segmentation with Deep ConvNets. 20-28 - Mohammad H. Jafari, Hany Girgis, Zhibin Liao, Delaram Behnami, Amir H. Abdi, Hooman Vaseli, Christina Luong, Robert Rohling, Ken Gin, Teresa Tsang, Purang Abolmaesumi:
A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data. 29-37 - Liying Peng, Lanfen Lin, Hongjie Hu, Huali Li, Qingqing Chen, Dan Wang, Xian-Hua Han, Yutaro Iwamoto, Yen-Wei Chen:
Multi-scale Residual Network with Two Channels of Raw CT Image and Its Differential Excitation Component for Emphysema Classification. 38-46 - Mengliu Zhao, Ghassan Hamarneh:
TreeNet: Multi-loss Deep Learning Network to Predict Branch Direction for Extracting 3D Anatomical Trees. 47-55 - Zhou He, Siqi Bao, Albert C. S. Chung:
3D Deep Affine-Invariant Shape Learning for Brain MR Image Segmentation. 56-64 - Delaram Behnami, Christina Luong, Hooman Vaseli, Amir H. Abdi, Hany Girgis, Dale Hawley, Robert Rohling, Ken Gin, Purang Abolmaesumi, Teresa Tsang:
Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography. 65-73 - Lihao Liu, Qi Dou, Hao Chen, Iyiola E. Olatunji, Jing Qin, Pheng-Ann Heng:
MTMR-Net: Multi-task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis. 74-82 - Jamshid Sourati, Ali Gholipour, Jennifer G. Dy, Sila Kurugol, Simon K. Warfield:
Active Deep Learning with Fisher Information for Patch-Wise Semantic Segmentation. 83-91 - Zhenlin Xu, Zhengyang Shen, Marc Niethammer:
Contextual Additive Networks to Efficiently Boost 3D Image Segmentations. 92-100 - Julian Krebs, Tommaso Mansi, Boris Mailhé, Nicholas Ayache, Hervé Delingette:
Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration. 101-109 - Lee B. Reid, Alex M. Pagnozzi:
Rapid Training Data Generation for Tissue Segmentation Using Global Approximate Block-Matching with Self-organizing Maps. 110-118 - Pei Wang, Albert C. S. Chung:
Focal Dice Loss and Image Dilation for Brain Tumor Segmentation. 119-127 - Roman Spilger, Thomas Wollmann, Yu Qiang, Andrea Imle, Ji Young Lee, Barbara Müller, Oliver T. Fackler, Ralf Bartenschlager, Karl Rohr:
Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning. 128-136 - Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu:
3D Convolutional Neural Networks for Classification of Functional Connectomes. 137-145 - Liesbeth Vandewinckele, David Robben, Wouter Crijns, Frederik Maes:
Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks. 146-154 - Lei Xiang, Yang Li, Weili Lin, Qian Wang, Dinggang Shen:
Unpaired Deep Cross-Modality Synthesis with Fast Training. 155-164 - Teresa Araújo, Guilherme Aresta, Adrian Galdran, Pedro Costa, Ana Maria Mendonça, Aurélio Campilho:
UOLO - Automatic Object Detection and Segmentation in Biomedical Images. 165-173 - Heran Yang, Jian Sun, Aaron Carass, Can Zhao, Junghoon Lee, Zongben Xu, Jerry L. Prince:
Unpaired Brain MR-to-CT Synthesis Using a Structure-Constrained CycleGAN. 174-182 - Firat Özdemir, Zixuan Peng, Christine Tanner, Philipp Fürnstahl, Orçun Göksel:
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy. 183-191 - Nicolas Toussaint, Bishesh Khanal, Matthew Sinclair, Alberto Gómez, Emily Skelton, Jacqueline Matthew, Julia A. Schnabel:
Weakly Supervised Localisation for Fetal Ultrasound Images. 192-200 - Thomas Varsavsky, Zach Eaton-Rosen, Carole H. Sudre, Parashkev Nachev, M. Jorge Cardoso:
PIMMS: Permutation Invariant Multi-modal Segmentation. 201-209 - Zara Alaverdyan, Jiazheng Chai, Carole Lartizien:
Unsupervised Feature Learning for Outlier Detection with Stacked Convolutional Autoencoders, Siamese Networks and Wasserstein Autoencoders: Application to Epilepsy Detection. 210-217 - Yechiel Lamash, Sila Kurugol, Simon K. Warfield:
Semi-automated Extraction of Crohns Disease MR Imaging Markers Using a 3D Residual CNN with Distance Prior. 218-226 - Shubham Kumar, Abhijit Guha Roy, Ping Wu, Sailesh Conjeti, R. S. Anand, Jian Wang, Igor Yakushev, Stefan Förster, Markus Schwaiger, Sung-Cheng Huang, Axel Rominger, Chuantao Zuo, Kuangyu Shi:
Learning Optimal Deep Projection of 18F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes. 227-235 - Yigit Baran Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu, Christian F. Baumgartner:
Learning to Segment Medical Images with Scribble-Supervision Alone. 236-244 - Aditya Sharma, Prabhjot Kaur, Aditya Nigam, Arnav Bhavsar:
Learning to Decode 7T-Like MR Image Reconstruction from 3T MR Images. 245-253 - Mayalen Etcheverry, Bogdan Georgescu, Benjamin Odry, Thomas J. Re, Shivam Kaushik, Bernhard Geiger, Mariappan S. Nadar, Sasa Grbic, Dorin Comaniciu:
Nonlinear Adaptively Learned Optimization for Object Localization in 3D Medical Images. 254-262 - Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P. Xing:
SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays. 263-273 - Marc Combalia, Verónica Vilaplana:
Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification. 274-281 - Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Demetri Terzopoulos, Nima Tajbakhsh:
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network. 282-290 - Meng Li, Shiwen Shen, Wen Gao, William Hsu, Jason Cong:
Computed Tomography Image Enhancement Using 3D Convolutional Neural Network. 291-299 - Vladimir I. Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin, Alexey A. Shvets:
Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks. 300-308 - Andreas Østvik, Erik Smistad, Torvald Espeland, Erik Andreas Rye Berg, Lasse Løvstakken:
Automatic Myocardial Strain Imaging in Echocardiography Using Deep Learning. 309-316 - Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. 317-325 - Ruggiero Santeramo, Samuel Withey, Giovanni Montana:
Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM. 326-333 - Danielle F. Pace, Adrian V. Dalca, Tom Brosch, Tal Geva, Andrew J. Powell, Jürgen Weese, Mehdi Hedjazi Moghari, Polina Golland:
Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease. 334-342 - Felix Lau, Tom Hendriks, Jesse Lieman-Sifry, Sean Sall, Daniel Golden:
ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans. 343-350
8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018
- Myra Cheng, Alfiia Galimzianova, Ziga Lesjak, Ziga Spiclin, Christopher B. Lock, Daniel L. Rubin:
A Multi-scale Multiple Sclerosis Lesion Change Detection in a Multi-sequence MRI. 353-360 - Haijun Lei, Yujia Zhao, Baiying Lei:
Multi-task Sparse Low-Rank Learning for Multi-classification of Parkinson's Disease. 361-368 - Sandip Sadhukhan, Goutam Kumar Ghorai, Souvik Maiti, Vikrant Anilrao Karale, Gautam Sarkar, Ashis Kumar Dhara:
Optic Disc Segmentation in Retinal Fundus Images Using Fully Convolutional Network and Removal of False-Positives Based on Shape Features. 369-376 - Hui Tang, Mehdi Moradi, Ken C. L. Wong, Hongzhi Wang, Ahmed El Harouni, Tanveer F. Syeda-Mahmood:
Integrating Deformable Modeling with 3D Deep Neural Network Segmentation. 377-384
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