default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLABELS/DLMIA@MICCAI 2016: Athens, Greece
- Gustavo Carneiro
, Diana Mateus, Loïc Peter, Andrew P. Bradley, João Manuel R. S. Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise:
Deep Learning and Data Labeling for Medical Applications - First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Lecture Notes in Computer Science 10008, 2016, ISBN 978-3-319-46975-1
Deep Learning in Medical Image Analysis
- Xian-Hua Han, Jianmei Lei, Yen-Wei Chen:
HEp-2 Cell Classification Using K-Support Spatial Pooling in Deep CNNs. 3-11 - Xiaoguang Lu, Daguang Xu, David Liu:
Robust 3D Organ Localization with Dual Learning Architectures and Fusion. 12-20 - Saad Ullah Akram, Juho Kannala, Lauri Eklund, Janne Heikkilä:
Cell Segmentation Proposal Network for Microscopy Image Analysis. 21-29 - Erik Smistad, Lasse Løvstakken:
Vessel Detection in Ultrasound Images Using Deep Convolutional Neural Networks. 30-38 - Khosro Bahrami, Feng Shi, Islem Rekik, Dinggang Shen:
Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features. 39-47 - Xiao Yang, Roland Kwitt, Marc Niethammer:
Fast Predictive Image Registration. 48-57 - Ariel Birenbaum, Hayit Greenspan:
Longitudinal Multiple Sclerosis Lesion Segmentation Using Multi-view Convolutional Neural Networks. 58-67 - Daniel E. Worrall, Clare M. Wilson, Gabriel J. Brostow:
Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks. 68-76 - Avi Ben-Cohen, Idit Diamant, Eyal Klang, Michal Amitai, Hayit Greenspan:
Fully Convolutional Network for Liver Segmentation and Lesions Detection. 77-85 - Youngjin Yoo, Lisa Y. W. Tang, Tom Brosch, David K. B. Li, Luanne Metz, Anthony Traboulsee, Roger C. Tam:
Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis. 86-94 - Ariel Benou, Ronel Veksler, Alon Friedman, Tammy Riklin Raviv:
De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks. 95-110 - Xiangrong Zhou, Takaaki Ito, Ryosuke Takayama, Song Wang, Takeshi Hara, Hiroshi Fujita:
Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting. 111-120 - Pavel Kisilev, Eli Sason, Ella Barkan, Sharbell Y. Hashoul:
Medical Image Description Using Multi-task-loss CNN. 121-129 - David Golan, Yoni Donner, Chris Mansi, Jacob L. Jaremko, Manoj Ramachandran:
Fully Automating Graf's Method for DDH Diagnosis Using Deep Convolutional Neural Networks. 130-141 - Simon Andermatt, Simon Pezold, Philippe C. Cattin:
Multi-dimensional Gated Recurrent Units for the Segmentation of Biomedical 3D-Data. 142-151 - Nico Hoffmann, Edmund Koch, Gerald Steiner, Uwe Petersohn, Matthias Kirsch:
Learning Thermal Process Representations for Intraoperative Analysis of Cortical Perfusion During Ischemic Strokes. 152-160 - Bob D. de Vos, Max A. Viergever, Pim A. de Jong, Ivana Isgum:
Automatic Slice Identification in 3D Medical Images with a ConvNet Regressor. 161-169 - Dong Nie, Xiaohuan Cao, Yaozong Gao, Li Wang, Dinggang Shen:
Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks. 170-178 - Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand, Samuel Kadoury, Chris Pal:
The Importance of Skip Connections in Biomedical Image Segmentation. 179-187 - Hariharan Ravishankar, Prasad Sudhakar, Rahul Venkataramani, Sheshadri Thiruvenkadam, Pavan Annangi, Narayanan Babu, Vivek Vaidya:
Understanding the Mechanisms of Deep Transfer Learning for Medical Images. 188-196 - Ayelet Akselrod-Ballin, Leonid Karlinsky, Sharon Alpert, Sharbell Y. Hasoul, Rami Ben-Ari, Ella Barkan:
A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography. 197-205
Large-Scale Annotation of Biomedical Data and Expert Label Synthesis
- Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo, Harm A. W. M. Tiddens, Marleen de Bruijne:
Early Experiences with Crowdsourcing Airway Annotations in Chest CT. 209-218 - Chi Liu, Yue Huang, Ligong Han, John A. Ozolek, Gustavo K. Rohde:
Hierarchical Feature Extraction for Nuclear Morphometry-Based Cancer Diagnosis. 219-227 - Alba Garcia Seco de Herrera, Roger Schaer, Sameer K. Antani, Henning Müller:
Using Crowdsourcing for Multi-label Biomedical Compound Figure Annotation. 228-237 - Valentina Carapella, Ernesto Jiménez-Ruiz, Elena Lukaschuk, Nay Aung, Kenneth Fung, José Miguel Paiva, Mihir Sanghvi, Stefan Neubauer, Steffen E. Petersen, Ian Horrocks, Stefan K. Piechnik:
Towards the Semantic Enrichment of Free-Text Annotation of Image Quality Assessment for UK Biobank Cardiac Cine MRI Scans. 238-248 - Stephen M. Plaza:
Focused Proofreading to Reconstruct Neural Connectomes from EM Images at Scale. 249-258 - Florian Dubost, Loïc Peter, Christian Rupprecht, Benjamín Gutiérrez-Becker, Nassir Navab:
Hands-Free Segmentation of Medical Volumes via Binary Inputs. 259-268 - Shadi Albarqouni, Stefan Matl, Maximilian Baust, Nassir Navab, Stefanie Demirci:
Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research. 269-277
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-10-31 20:23 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
