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ORCID6th MLMI@MICCAI 2015: Munich, Germany
- Luping Zhou, Li Wang, Qian Wang, Yinghuan Shi:
Machine Learning in Medical Imaging - 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings. Lecture Notes in Computer Science 9352, Springer 2015, ISBN 978-3-319-24887-5 - Suman Sedai
, Pallab Kanti Roy, Rahil Garnavi:
Segmentation of Right Ventricle in Cardiac MR Images Using Shape Regression. 1-8 - Dwarikanath Mahapatra, Joachim M. Buhmann:
Visual Saliency Based Active Learning for Prostate MRI Segmentation. 9-16 - Guangkai Ma, Yaozong Gao, Li Wang, Ligang Wu, Dinggang Shen:
Soft-Split Random Forest for Anatomy Labeling. 17-25 - Tao Xu, Cheng Xin, L. Rodney Long, Sameer K. Antani, Zhiyun Xue, Edward Kim, Xiaolei Huang:
A New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation. 26-35 - Benjamin S. C. Wade, Shantanu H. Joshi, Boris A. Gutman, Paul M. Thompson:
Machine Learning on High Dimensional Shape Data from Subcortical Brain Surfaces: A Comparison of Feature Selection and Classification Methods. 36-43 - Bernard Ng, Anna-Clare Milazzo, André Altmann:
Node-Based Gaussian Graphical Model for Identifying Discriminative Brain Regions from Connectivity Graphs. 44-51 - Mohammad Khatami, Tobias Schmidt-Wilcke, Pia C. Sundgren, Amin Abbasloo, Bernhard Schölkopf, Thomas Schultz:
BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease. 52-60 - Marta Nuñez Garcia, Sonja Simpraga, María Ángeles Jurado, Maite Garolera, Roser Pueyo, Laura Igual:
FADR: Functional-Anatomical Discriminative Regions for Rest fMRI Characterization. 61-68 - Zuoyong Li, Le An, Jun Zhang, Li Wang, James J. Xia, Dinggang Shen:
Craniomaxillofacial Deformity Correction via Sparse Representation in Coherent Space. 69-76 - Tong Tong, Katherine R. Gray, Qinquan Gao, Liang Chen, Daniel Rueckert:
Nonlinear Graph Fusion for Multi-modal Classification of Alzheimer's Disease. 77-84 - Xian-Hua Han, Yen-Wei Chen, Gang Xu:
HEp-2 Staining Pattern Recognition Using Stacked Fisher Network for Encoding Weber Local Descriptor. 85-93 - Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker:
Supervoxel Classification Forests for Estimating Pairwise Image Correspondences. 94-101 - Guoyan Zheng, Weimin Yu:
Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model. 102-109 - Veronika A. M. Zimmer, Ben Glocker, Paul Aljabar, Serena J. Counsell, Mary A. Rutherford, A. David Edwards, Joseph V. Hajnal, Miguel Ángel González Ballester, Daniel Rueckert, Gemma Piella:
Learning and Combining Image Similarities for Neonatal Brain Population Studies. 110-117 - Noel Codella, Junjie Cai, Mani Abedini, Rahil Garnavi, Alan Halpern, John R. Smith:
Deep Learning, Sparse Coding, and SVM for Melanoma Recognition in Dermoscopy Images. 118-126 - Yan Wang, Pei Zhang, Le An, Guangkai Ma, Jiayin Kang, Xi Wu, Jiliu Zhou, David S. Lalush, Weili Lin, Dinggang Shen:
Predicting Standard-Dose PET Image from Low-Dose PET and Multimodal MR Images Using Mapping-Based Sparse Representation. 127-135 - Julian G. Zilly, Joachim M. Buhmann, Dwarikanath Mahapatra:
Boosting Convolutional Filters with Entropy Sampling for Optic Cup and Disc Image Segmentation from Fundus Images. 136-143 - Kuldeep Kumar, Christian Desrosiers, Kaleem Siddiqi:
Brain Fiber Clustering Using Non-negative Kernelized Matching Pursuit. 144-152 - Atsuki Masuda, Bisser Raytchev, Takio Kurita, Toru Imamura, Masashi Suzuki, Toru Tamaki, Kazufumi Kaneda:
Automatic Detection of Good/Bad Colonies of iPS Cells Using Local Features. 153-160 - Aisha Khan, Stephen Gould, Mathieu Salzmann:
Detecting Abnormal Cell Division Patterns in Early Stage Human Embryo Development. 161-169 - Yan Jin, Chong-Yaw Wee, Feng Shi, Kim-Han Thung, Pew-Thian Yap, Dinggang Shen:
Identification of Infants at Risk for Autism Using Multi-parameter Hierarchical White Matter Connectomes. 170-177 - Ricardo Guerrero, Christian Ledig, Alexander Schmidt-Richberg, Daniel Rueckert:
Group-Constrained Laplacian Eigenmaps: Longitudinal AD Biomarker Learning. 178-185 - Qin Liu, Qian Wang, Lichi Zhang, Yaozong Gao, Dinggang Shen:
Multi-atlas Context Forests for Knee MR Image Segmentation. 186-193 - Snehashis Roy, Aaron Carass, Jerry L. Prince, Dzung L. Pham:
Longitudinal Patch-Based Segmentation of Multiple Sclerosis White Matter Lesions. 194-202 - Hongkun Ge, Guorong Wu, Li Wang, Yaozong Gao, Dinggang Shen:
Hierarchical Multi-modal Image Registration by Learning Common Feature Representations. 203-211 - Pierre-Henri Conze, François Rousseau, Vincent Noblet, Fabrice Heitz, Riccardo Memeo, Patrick Pessaux:
Semi-automatic Liver Tumor Segmentation in Dynamic Contrast-Enhanced CT Scans Using Random Forests and Supervoxels. 212-219 - Gustavo Carneiro, Tingying Peng, Christine Bayer, Nassir Navab:
Flexible and Latent Structured Output Learning - Application to Histology. 220-228 - Davy Vanderweyen, Brent C. Munsell, Jacobo E. Mintzer, Olga Mintzer, Andy Gajadhar, Xun Zhu, Guorong Wu, Jane E. Joseph:
Identifying Abnormal Network Alterations Common to Traumatic Brain Injury and Alzheimer's Disease Patients Using Functional Connectome Data. 229-237 - Bo Cheng, Mingxia Liu, Daoqiang Zhang:
Multimodal Multi-label Transfer Learning for Early Diagnosis of Alzheimer's Disease. 238-245 - Lei Huang, Yaozong Gao, Yan Jin, Kim-Han Thung, Dinggang Shen:
Soft-Split Sparse Regression Based Random Forest for Predicting Future Clinical Scores of Alzheimer's Disease. 246-254 - Xiaofeng Zhu, Heung-Il Suk, Yonghua Zhu, Kim-Han Thung, Guorong Wu, Dinggang Shen:
Multi-view Classification for Identification of Alzheimer's Disease. 255-262 - Mohammad Peikari, Judit T. Zubovits, Gina M. Clarke, Anne L. Martel:
Clustering Analysis for Semi-supervised Learning Improves Classification Performance of Digital Pathology. 263-270 - Yanling Chi, Weimin Huang, Jiayin Zhou, Liang Zhong, Swee Yaw Tan, Keng Yung Jih Felix, Low Choon Seng Sheon, Ru-San Tan:
A Composite of Features for Learning-Based Coronary Artery Segmentation on Cardiac CT Angiography. 271-279 - Michaela Weingant, Hayley M. Reynolds, Annette Haworth, Catherine Mitchell, Scott Williams, Matthew D. DiFranco:
Ensemble Prostate Tumor Classification in H&E Whole Slide Imaging via Stain Normalization and Cell Density Estimation. 280-287 - Jiawen Yao, Dheeraj Ganti, Xin Luo, Guanghua Xiao, Yang Xie, Shirley Yan, Junzhou Huang:
Computer-Assisted Diagnosis of Lung Cancer Using Quantitative Topology Features. 288-295 - Mingxia Liu, Daoqiang Zhang, Dinggang Shen:
Inherent Structure-Guided Multi-view Learning for Alzheimer's Disease and Mild Cognitive Impairment Classification. 296-303 - Yani Chen, Bibo Shi, Charles D. Smith, Jundong Liu:
Nonlinear Feature Transformation and Deep Fusion for Alzheimer's Disease Staging Analysis. 304-312 - Xiao Liu, Jun Shi, Qi Zhang:
Tumor Classification by Deep Polynomial Network and Multiple Kernel Learning on Small Ultrasound Image Dataset. 313-320 - Tri Huynh, Yaozong Gao, Jiayin Kang, Li Wang, Pei Zhang, Dinggang Shen:
Multi-source Information Gain for Random Forest: An Application to CT Image Prediction from MRI Data. 321-329 - Bai Ying Lei, Siping Chen, Dong Ni, Tianfu Wang:
Joint Learning of Multiple Longitudinal Prediction Models by Exploring Internal Relations. 330-337
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