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ORCID1st PRIME@MICCAI 2018: Granada, Spain
- Islem Rekik, Gözde B. Ünal, Ehsan Adeli
, Sang Hyun Park:
PRedictive Intelligence in MEdicine - First International Workshop, PRIME 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11121, Springer 2018, ISBN 978-3-030-00319-7 - Gudmundur Einarsson, Line Katrine Harder Clemmensen, Ditte Rudå, Anders Fink-Jensen, Jannik Boll Nielsen, Anne Katrine Pagsberg, Kristian Winge, Rasmus R. Paulsen:
Computer Aided Identification of Motion Disturbances Related to Parkinson's Disease. 1-8 - Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Pamela Ventola, James S. Duncan:
Prediction of Severity and Treatment Outcome for ASD from fMRI. 9-17 - Euijin Jung, Xiaopeng Zong, Weili Lin, Dinggang Shen, Sanghyun Park:
Enhancement of Perivascular Spaces Using a Very Deep 3D Dense Network. 18-25 - Yu Yan, Hoileong Lee, Edward Somer, Vicente Grau:
Generation of Amyloid PET Images via Conditional Adversarial Training for Predicting Progression to Alzheimer's Disease. 26-33 - Muhammad Ilyas, Alice Othmani, Amine Naït-Ali:
Prediction of Hearing Loss Based on Auditory Perception: A Preliminary Study. 34-41 - Thomas Janssoone, Pierre Rinder, Pierre Hornus, Dorra Kanoun:
Predictive Patient Care: Survival Model to Prevent Medication Non-adherence. 42-50 - Kim-Han Thung, Pew-Thian Yap, Dinggang Shen:
Joint Robust Imputation and Classification for Early Dementia Detection Using Incomplete Multi-modality Data. 51-59 - Adrià Casamitjana, Verónica Vilaplana, Paula M. Petrone, José Luis Molinuevo, Juan Domingo Gispert:
Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer's Disease. 60-67 - Hennadii Madan, Rok Berlot, Nicola J. Ray, Franjo Pernus, Ziga Spiclin:
Predicting Nucleus Basalis of Meynert Volume from Compartmental Brain Segmentations. 68-75 - Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, Dinggang Shen:
Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis. 76-84 - Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, Taku Komura:
Transfer Learning for Task Adaptation of Brain Lesion Assessment and Prediction of Brain Abnormalities Progression/Regression Using Irregularity Age Map in Brain MRI. 85-93 - Minghui Zhu, Islem Rekik:
Multi-view Brain Network Prediction from a Source View Using Sample Selection via CCA-Based Multi-kernel Connectomic Manifold Learning. 94-102 - Anna Lisowska, Islem Rekik:
Predicting Emotional Intelligence Scores from Multi-session Functional Brain Connectomes. 103-111 - Maryamossadat Aghili, Solale Tabarestani, Malek Adjouadi, Ehsan Adeli:
Predictive Modeling of Longitudinal Data for Alzheimer's Disease Diagnosis Using RNNs. 112-119 - Victor Martin, Renaud Séguier, Aurélie Porcheron, Frédérique Morizot:
Towards Continuous Health Diagnosis from Faces with Deep Learning. 120-128 - Sophia Bano, Muhammad Asad, Ahmed E. Fetit, Islem Rekik:
XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference. 129-137 - Chiyu Feng, Ahmed El-Azab, Peng Yang, Tianfu Wang, Baiying Lei, Xiaohua Xiao:
3D Convolutional Neural Network and Stacked Bidirectional Recurrent Neural Network for Alzheimer's Disease Diagnosis. 138-146 - Sahin Olut, Yusuf Huseyin Sahin, Ugur Demir, Gözde B. Ünal:
Generative Adversarial Training for MRA Image Synthesis Using Multi-contrast MRI. 147-154 - Enes Albay, Ugur Demir, Gözde B. Ünal:
Diffusion MRI Spatial Super-Resolution Using Generative Adversarial Networks. 155-163 - Jungrae Cho, Yoon-Nyun Kim, Minho Lee:
Prediction to Atrial Fibrillation Using Deep Convolutional Neural Networks. 164-171
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