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ORCIDMedical Image Analysis, Volume 58
Volume 58, December 2019
- Mengyu Dai
, Zhengwu Zhang, Anuj Srivastava:
Discovering common change-point patterns in functional connectivity across subjects. - Zhifan Gao, Sitong Wu, Zhi Liu, Jianwen Luo, Heye Zhang, Mingming Gong, Shuo Li:
Learning the implicit strain reconstruction in ultrasound elastography using privileged information. - Shen Zhao, Xi Wu, Bo Chen, Shuo Li:
Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network. - Leonid Kostrykin, Christoph Schnörr, Karl Rohr:
Globally optimal segmentation of cell nuclei in fluorescence microscopy images using shape and intensity information. - Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert:
Self-supervised learning for medical image analysis using image context restoration. - Darko Stern, Christian Payer, Martin Urschler:
Automated age estimation from MRI volumes of the hand. - Sahar Ahmad, Zhengwang Wu, Gang Li, Li Wang, Weili Lin, Pew-Thian Yap, Dinggang Shen:
Surface-constrained volumetric registration for the early developing brain. - Nima Tajbakhsh, Jae Y. Shin, Michael B. Gotway, Jianming Liang:
Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. - Xiahai Zhuang, Lei Li, Christian Payer, Darko Stern, Martin Urschler, Mattias P. Heinrich, Julien Oster, Chunliang Wang, Örjan Smedby, Cheng Bian, Xin Yang, Pheng-Ann Heng, Aliasghar Mortazi, Ulas Bagci, Guanyu Yang, Chenchen Sun, Gaetan Galisot, Jean-Yves Ramel, Guang Yang:
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge. - Zaneta Swiderska-Chadaj, Hans Pinckaers, Mart van Rijthoven, Maschenka Balkenhol, Margarita Melnikova, Oscar Geessink, Quirine Manson, Mark Sherman, António Polónia, Jeremy Parry, Mustapha Abubakar, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Learning to detect lymphocytes in immunohistochemistry with deep learning. - David Tellez, Geert Litjens, Péter Bándi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak:
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. - Liansheng Wang, Qiuhao Xu, Stephanie Leung, Jonathan Chung, Bo Chen, Shuo Li:
Accurate automated Cobb angles estimation using multi-view extrapolation net. - Shujun Wang, Yaxi Zhu, Lequan Yu, Hao Chen, Huangjing Lin, Xiangbo Wan, Xinjuan Fan, Pheng-Ann Heng:
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification. - Xin Yi, Ekta Walia, Paul S. Babyn:
Generative adversarial network in medical imaging: A review. - Tianjiao Liu, Qianqian Guo, Chunfeng Lian, Xuhua Ren, Shujun Liang, Jing Yu, Lijuan Niu, Weidong Sun, Dinggang Shen:
Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks. - Jianing Wang, Jack H. Noble, Benoit M. Dawant:
Metal artifact reduction for the segmentation of the intra cochlear anatomy in CT images of the ear with 3D-conditional GANs. - Zehui Lin, Shengli Li, Dong Ni, Yimei Liao, Huaxuan Wen, Jie Du, Siping Chen, Tianfu Wang, Baiying Lei:
Multi-task learning for quality assessment of fetal head ultrasound images. - Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Kyoung Mu Lee:
Deep vessel segmentation by learning graphical connectivity. - Nooshin Ghavami, Yipeng Hu, Eli Gibson, Ester Bonmati, Mark Emberton, Caroline M. Moore, Dean C. Barratt:
Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration. - Rongjun Ge, Guanyu Yang, Yang Chen, Limin Luo, Cheng Feng, Heye Zhang, Shuo Li:
PV-LVNet: Direct left ventricle multitype indices estimation from 2D echocardiograms of paired apical views with deep neural networks. - Ze Jin, Jayaram K. Udupa, Drew A. Torigian:
How many models/atlases are needed as priors for capturing anatomic population variations? - Simon Graham, Quoc Dang Vu, Shan E Ahmed Raza, Ayesha Azam, Yee-Wah Tsang, Jin Tae Kwak, Nasir M. Rajpoot:
Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images. - Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro:
Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI. - Agisilaos Chartsias, Thomas Joyce, Giorgos Papanastasiou, Scott Semple, Michelle C. Williams, David E. Newby, Rohan Dharmakumar, Sotirios A. Tsaftaris:
Disentangled representation learning in cardiac image analysis.
- Julia A. Schnabel, Christos Davatzikos, Gabor Fichtinger, Alejandro F. Frangi, Carlos Alberola-López:
Special issue on MICCAI 2018. - Jingfan Fan, Xiaohuan Cao, Qian Wang, Pew-Thian Yap, Dinggang Shen:
Adversarial learning for mono- or multi-modal registration. - Wen Wei, Emilie Poirion, Benedetta Bodini, Stanley Durrleman, Nicholas Ayache, Bruno Stankoff, Olivier Colliot:
Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis. - Pierre-Antoine Ganaye, Michaël Sdika, Bill Triggs, Hugues Benoit-Cattin:
Removing segmentation inconsistencies with semi-supervised non-adjacency constraint. - Jakob Wasserthal, Peter F. Neher, Dusan Hirjak, Klaus H. Maier-Hein:
Combined tract segmentation and orientation mapping for bundle-specific tractography.
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