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ORCIDRAMBO+BIA+TIA@MICCAI 2018: Granada, Spain
- Danail Stoyanov, Zeike Taylor, Bernhard Kainz, Gabriel Maicas, Reinhard R. Beichel, Anne L. Martel, Lena Maier-Hein, Kanwal K. Bhatia, Tom Vercauteren, Ozan Oktay, Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, Hang Min, Matthew S. Brown, Colin Jacobs, Bianca Lassen-Schmidt, Kensaku Mori, Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Catarina Veiga:
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. Lecture Notes in Computer Science 11040, Springer 2018, ISBN 978-3-030-00945-8
Third International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2018
- Marek Wodzinski
, Andrzej Skalski:
Resection-Based Demons Regularization for Breast Tumor Bed Propagation. 3-12 - Stergios Christodoulidis, Mihir Sahasrabudhe, Maria Vakalopoulou, Guillaume Chassagnon, Marie-Pierre Revel, Stavroula G. Mougiakakou, Nikos Paragios:
Linear and Deformable Image Registration with 3D Convolutional Neural Networks. 13-22 - Nicolas Basty, Vicente Grau:
Super Resolution of Cardiac Cine MRI Sequences Using Deep Learning. 23-31 - Eric Kerfoot, Esther Puyol-Antón, Bram Ruijsink, James R. Clough, Andrew P. King, Julia A. Schnabel:
Automated CNN-Based Reconstruction of Short-Axis Cardiac MR Sequence from Real-Time Image Data. 32-41 - Mia Mojica, Mehran Ebrahimi:
An Unbiased Groupwise Registration Algorithm for Correcting Motion in Dynamic Contrast-Enhanced Magnetic Resonance Images. 42-52
Fourth International Workshop on Breast Image Analysis, BIA 2018
- Shaked Perek, Alon Hazan, Ella Barkan, Ayelet Akselrod-Ballin:
Siamese Network for Dual-View Mammography Mass Matching. 55-63 - Stephen Morrell, Zbigniew Wojna, Can Son Khoo, Sébastien Ourselin, Juan Eugenio Iglesias:
Large-Scale Mammography CAD with Deformable Conv-Nets. 64-72 - Jennifer Kamphenkel, Paul F. Jäger, Sebastian Bickelhaupt, Frederik Bernd Laun, Wolfgang Lederer, Heidi Daniel, Tristan Anselm Kuder, Stefan Delorme, Heinz-Peter Schlemmer, Franziska König, Klaus H. Maier-Hein:
Domain Adaptation for Deviating Acquisition Protocols in CNN-Based Lesion Classification on Diffusion-Weighted MR Images. 73-80 - Heyi Li, Dongdong Chen, William H. Nailon, Mike E. Davies, David Laurenson:
Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-Net. 81-89 - Yeman Brhane Hagos, Albert Gubern-Mérida, Jonas Teuwen:
Improving Breast Cancer Detection Using Symmetry Information with Deep Learning. 90-97 - Eric Wu, Kevin Wu, David D. Cox, William Lotter:
Conditional Infilling GANs for Data Augmentation in Mammogram Classification. 98-106 - Rongzhao Zhang, Han Zhang, Albert C. S. Chung:
A Unified Mammogram Analysis Method via Hybrid Deep Supervision. 107-115 - Songtao Zhang, Li Sun, Ruiqiao Wang, Hongping Tang, Jin Zhang, Lin Luo:
Structure-Aware Staging for Breast Cancer Metastases. 116-123 - Ignacio A. Illán, Javier Ramírez, J. M. Górriz, Katja Pinker-Domenig, Anke Meyer-Baese:
Reproducible Evaluation of Registration Algorithms for Movement Correction in Dynamic Contrast Enhancing Magnetic Resonance Imaging for Breast Cancer Diagnosis. 124-131
First International Workshop on Thoracic Image Analysis, TIA 2018
- Santiago Sanz-Estébanez, Lucilio Cordero-Grande, Marcos Martín-Fernández, Carlos Alberola-López:
Robust Windowed Harmonic Phase Analysis with a Single Acquisition. 135-146 - Ophir Gozes, Hayit Greenspan:
Lung Structures Enhancement in Chest Radiographs via CT Based FCNN Training. 147-158 - Maayan Frid-Adar, Avi Ben-Cohen, Rula Amer, Hayit Greenspan:
Improving the Segmentation of Anatomical Structures in Chest Radiographs Using U-Net with an ImageNet Pre-trained Encoder. 159-168 - Ana Ortega-Gil, Arrate Muñoz-Barrutia, Laura Fernandez-Terron, Juan José Vaquero:
Tuberculosis Histopathology on X Ray CT. 169-179 - Gonzalo Vegas-Sánchez-Ferrero, Raúl San José Estépar:
A CT Scan Harmonization Technique to Detect Emphysema and Small Airway Diseases. 180-190 - Sarah E. Gerard, Jacob Herrmann, David W. Kaczka, Joseph M. Reinhardt:
Transfer Learning for Segmentation of Injured Lungs Using Coarse-to-Fine Convolutional Neural Networks. 191-201 - Xiaoyong Wang, Pangyu Teng, Pechin Lo, Ashley Banola, Grace H. Kim, Fereidoun Abtin, Jonathan G. Goldin, Matthew S. Brown:
High Throughput Lung and Lobar Segmentation by 2D and 3D CNN on Chest CT with Diffuse Lung Disease. 202-214 - Germán González, George R. Washko, Raúl San José Estépar:
Multi-structure Segmentation from Partially Labeled Datasets. Application to Body Composition Measurements on CT Scans. 215-224 - Karen López-Linares Román, Isaac de La Bruere, Jorge Onieva, Lasse Andresen, Jakob Qvortrup Holsting, Farbod N. Rahaghi, Iván Macía, Miguel Ángel González Ballester, Raúl San José Estépar:
3D Pulmonary Artery Segmentation from CTA Scans Using Deep Learning with Realistic Data Augmentation. 225-237 - A. Garcia-Uceda Juarez, Harm A. W. M. Tiddens, Marleen de Bruijne:
Automatic Airway Segmentation in Chest CT Using Convolutional Neural Networks. 238-250 - Wei Shao, Taylor J. Patton, Sarah E. Gerard, Yue Pan, Joseph M. Reinhardt, John E. Bayouth, Oguz C. Durumeric, Gary E. Christensen:
Detecting Out-of-Phase Ventilation Using 4DCT to Improve Radiation Therapy for Lung Cancer. 251-259 - Adam Szmul, Tahreema N. Matin, Fergus V. Gleeson, Julia A. Schnabel, Vicente Grau, Bartlomiej W. Papiez:
XeMRI to CT Lung Image Registration Enhanced with Personalized 4DCT-Derived Motion Model. 260-271 - Sonja Jäckle, Stefan Heldmann:
Rigid Lens - Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scans. 272-283 - Jorge Onieva Onieva, Berta Martí Fuster, María Pedrero de la Puente, Raúl San José Estépar:
Diffeomorphic Lung Registration Using Deep CNNs and Reinforced Learning. 284-294 - William Lindsay, Jiancong Wang, Nicholas Sachs, Eduardo Barbosa, James C. Gee:
Transfer Learning Approach to Predict Biopsy-Confirmed Malignancy of Lung Nodules from Imaging Data: A Pilot Study. 295-301 - Charles R. Hatt, Craig J. Galbán, Wassim Labaki, Ella A. Kazerooni, David Lynch, Meilan Han:
Convolutional Neural Network Based COPD and Emphysema Classifications Are Predictive of Lung Cancer Diagnosis. 302-309 - Guilherme Aresta, Teresa Araújo, Colin Jacobs, Bram van Ginneken, António Cunha, Isabel Ramos, Aurélio Campilho:
Towards an Automatic Lung Cancer Screening System in Low Dose Computed Tomography. 310-318 - Stephen M. Humphries, Aleena M. Notary, Juan Pablo Centeno, David A. Lynch:
Automatic Classification of Centrilobular Emphysema on CT Using Deep Learning: Comparison with Visual Scoring. 319-325 - Carlos Cano-Espinosa, Germán González, George R. Washko, Miguel Cazorla, Raúl San José Estépar:
On the Relevance of the Loss Function in the Agatston Score Regression from Non-ECG Gated CT Scans. 326-334 - Pietro Nardelli, Mathias Buus Lanng, Cecilie Brochdorff Møller, Anne-Sofie Hendrup Andersen, Alex Skovsbo Jørgensen, Lasse Riis Østergaard, Raúl San José Estépar:
Accurate Measurement of Airway Morphology on Chest CT Images. 335-347
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