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ORCIDMedical Image Analysis, Volume 54
Volume 54, May 2019
- Mattias P. Heinrich
, Ozan Oktay, Nassim Bouteldja:
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions. 1-9 - Jianpeng Zhang, Yutong Xie, Qi Wu, Yong Xia:
Medical image classification using synergic deep learning. 10-19 - Neerav Karani, Lin Zhang, Christine Tanner, Ender Konukoglu:
An image interpolation approach for acquisition time reduction in navigator-based 4D MRI. 20-29 - Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Georg Langs, Ursula Schmidt-Erfurth:
f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks. 30-44 - Xingyu Wu, Jayaram K. Udupa, Yubing Tong, Dewey Odhner, Gargi V. Pednekar, Charles B. Simone II, David McLaughlin, Chavanon Apinorasethkul, Ontida Apinorasethkul, John Lukens, Dimitris Mihailidis, Geraldine Shammo, Paul James, Akhil Tiwari, Lisa Wojtowicz, Joseph Camaratta, Drew A. Torigian:
AAR-RT - A system for auto-contouring organs at risk on CT images for radiation therapy planning: Principles, design, and large-scale evaluation on head-and-neck and thoracic cancer cases. 45-62 - Abhay Shah, Michael D. Abràmoff, Xiaodong Wu:
Optimal surface segmentation with convex priors in irregularly sampled space. 63-75 - Eloy García, Yago Diez, Oliver Díaz, Xavier Lladó, Albert Gubern-Mérida, Robert Martí, Joan Martí, Arnau Oliver:
Breast MRI and X-ray mammography registration using gradient values. 76-87 - Hoel Kervadec, Jose Dolz, Meng Tang, Eric Granger, Yuri Boykov, Ismail Ben Ayed:
Constrained-CNN losses for weakly supervised segmentation. 88-99 - Donghuan Lu, Morgan Heisler, Sieun Lee, Gavin Weiguang Ding, Eduardo Navajas, Marinko V. Sarunic, Mirza Faisal Beg:
Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network. 100-110 - Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge. 111-121 - Jiaqi Sun, Alireza Entezari, Baba C. Vemuri:
Exploiting structural redundancy in q-space for improved EAP reconstruction from highly undersampled (k, q)-space in DMRI. 122-137 - Mehdi Rahim, Bertrand Thirion, Gaël Varoquaux:
Population shrinkage of covariance (PoSCE) for better individual brain functional-connectivity estimation. 138-148 - Maria Antico, Fumio Sasazawa, Liao Wu, Anjali Tumkur Jaiprakash, Jonathan Roberts, Ross Crawford, Ajay K. Pandey, Davide Fontanarosa:
Ultrasound guidance in minimally invasive robotic procedures. 149-167 - Shuai Wang, Kelei He, Dong Nie, Sihang Zhou, Yaozong Gao, Dinggang Shen:
CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation. 168-178 - Serife Seda Kucur, Pablo Márquez-Neila, Mathias Abegg, Raphael Sznitman:
Patient-attentive sequential strategy for perimetry-based visual field acquisition. 179-192 - Jingfan Fan, Xiaohuan Cao, Pew-Thian Yap, Dinggang Shen:
BIRNet: Brain image registration using dual-supervised fully convolutional networks. 193-206 - Christian Payer, Darko Stern, Horst Bischof, Martin Urschler:
Integrating spatial configuration into heatmap regression based CNNs for landmark localization. 207-219 - Mikael Agn, Per Munck af Rosenschöld, Oula Puonti, Michael J. Lundemann, Laura Mancini, Anastasia Papadaki, Steffi Thust, John Ashburner, Ian Law, Koen Van Leemput:
A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning. 220-237 - Shu Zhang, Qinglin Dong, Wei Zhang, Heng Huang, Dajiang Zhu, Tianming Liu:
Discovering hierarchical common brain networks via multimodal deep belief network. 238-252 - Ida Häggström, Charles Ross Schmidtlein, Gabriele Campanella, Thomas J. Fuchs:
DeepPET: A deep encoder-decoder network for directly solving the PET image reconstruction inverse problem. 253-262 - Jordina Torrents-Barrena, Gemma Piella, Narcís Masoller, Eduard Gratacós, Elisenda Eixarch, Mario Ceresa, Miguel Ángel González Ballester:
Fully automatic 3D reconstruction of the placenta and its peripheral vasculature in intrauterine fetal MRI. 263-279 - Veronika Cheplygina, Marleen de Bruijne, Josien P. W. Pluim:
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis. 280-296 - Karthik Gopinath, Christian Desrosiers, Herve Lombaert:
Graph Convolutions on Spectral Embeddings for Cortical Surface Parcellation. 297-305 - Peng Liu, Mohammad D. El Basha, Yangjunyi Li, Yao Xiao, Pina C. Sanelli, Ruogu Fang:
Deep Evolutionary Networks with Expedited Genetic Algorithms for Medical Image Denoising. 306-315
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