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A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A.W.M. van der Laak, Bram van Ginneken, Clara I. Sánchez
2017 Medical Image Analysis  
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images.  ...  We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area.  ...  ArXiv was searched for papers mentioning one of a set of terms related to medical imaging.  ... 
doi:10.1016/ pmid:28778026 fatcat:esbj72ftwvbgzh6jgw367k73j4

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

José Ignacio Orlando, Huazhu Fu, João Barbossa Breda, Karel van Keer, Deepti R. Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, JoonHo Lee, Joonseok Lee, Xiaoxiao Li (+19 others)
2019 Medical Image Analysis  
Deep learning approaches, although widely applied for medical image analysis, have not been extensively used for glaucoma assessment due to the limited size of the available data sets.  ...  Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders.  ...  However, the resulting labels should be afterwards transferred to CFP e.g. via image registration, which might be subject to errors if the registration algorithm fails.  ... 
doi:10.1016/ pmid:31630011 fatcat:lh2i5zmlrvhxdp25333pwxkvry

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation [article]

Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, Jorge Cardoso, Marc Modat, Kayhan Batmanghelich, Arseniy Belkov, Maria Baldeon Calisto (+28 others)
2022 arXiv   pre-print
A segmentation network was then trained using these generated images and the manual annotations provided for the source image.  ...  CrossMoDA is the first large and multi-class benchmark for unsupervised cross-modality DA.  ...  A complete review of DA for medical image analysis can be found in Guan and Liu (2021) . Unsupervised DA (UDA) has especially raised attention as it doesn't require any additional annotations.  ... 
arXiv:2201.02831v2 fatcat:qdd3rj62czdmxjwinmif7mkay4

Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19

Hanan Farhat, George E. Sakr, Rima Kilany
2020 Machine Vision and Applications  
Yet, coronavirus can be the real trigger to open the route for fast integration of DL in hospitals and medical centers.  ...  Shortly after deep learning algorithms were applied to Image Analysis, and more importantly to medical imaging, their applications increased significantly to become a trend.  ...  Besides, it states the future research directions as follows: deep adversarial image registration, reinforcement learning-based registration, and raw imaging domain registration.  ... 
doi:10.1007/s00138-020-01101-5 pmid:32834523 pmcid:PMC7386599 fatcat:tkkylrptc5hkpoj52hjs3kuttu

A review of atlas-based segmentation for magnetic resonance brain images

Mariano Cabezas, Arnau Oliver, Xavier Lladó, Jordi Freixenet, Meritxell Bach Cuadra
2011 Computer Methods and Programs in Biomedicine  
In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction.  ...  In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images.  ...  This study is also supported by the Center for Biomedical Imaging (CIBM) of the Geneva and Lausanne Universities and the EPFL, as well as the Leenaards and Louis Jeantet foundations.  ... 
doi:10.1016/j.cmpb.2011.07.015 pmid:21871688 fatcat:b4k343jqvbccjj2ps5lpqb2raq

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
DAY 2 -Jan 13, 2021 Lan, Sheng; Guo, Zhenhua 47 A Joint Super-Resolution and Deformable Registration Network for 3D Brain Images DAY 2 -Jan 13, 2021 Matsumi, Susumu; Yamada, Keiichi 54 Few-Shot  ...  , Xiaoyi 2990 3D Point Cloud Registration Based on Cascaded Mutual Information Attention Network DAY 3 -Jan 14, 2021 -DAY 3 -Jan 14, 2021 Shemer, Yair; Rotman, Daniel; Shimkin, Nahum 504 OS  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

The Liver Tumor Segmentation Benchmark (LiTS) [article]

Patrick Bilic, Patrick Ferdinand Christ, Eugene Vorontsov, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, Samuel Kadoury, Tomasz Konopczyǹski (+44 others)
2019 arXiv   pre-print
Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017.  ...  We found that not a single algorithm performed best for liver and tumors.  ...  Park et al. proposed the first PA utilizing 32 abdominal CT series for registration based on mutual information and thin plate splines as warping transformations [32] and a Markov random field (MRF)  ... 
arXiv:1901.04056v1 fatcat:25ekt2znl5adnd5laap4ez6a4y

Image Matching from Handcrafted to Deep Features: A Survey

Jiayi Ma, Xingyu Jiang, Aoxiang Fan, Junjun Jiang, Junchi Yan
2020 International Journal of Computer Vision  
Secondly, we briefly introduce several typical image matching-based applications for a comprehensive understanding of the significance of image matching.  ...  This survey can serve as a reference for (but not limited to) researchers and engineers in image matching and related fields.  ...  Arar et al. (2020) introduced an unsupervised multi-modal image registration technique based on an image-to-image translation network with geometric preserving constraints.  ... 
doi:10.1007/s11263-020-01359-2 fatcat:a2epfaolwjfm5mcrsmn7g6sd7m

Author Index

2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
Workshop: Local Concept-Based Medical Image Retrieval with Correlation-Enhanced Similarity Matching Based on Global Analysis Thompson, Paul Compression of Surface Registrations using Beltrami Coefficients  ...  : A Tumor Growth Modeling Based Approach Workshop: Learning High-dimensional Image Statistics for Aabnormality Detection on Medical Images Workshop: Application of Trace-Norm and Low-Rank Matrix Decomposition  ... 
doi:10.1109/cvpr.2010.5539913 fatcat:y6m5knstrzfyfin6jzusc42p54

Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest

Christian Debes, Andreas Merentitis, Roel Heremans, Jurgen Hahn, Nikolaos Frangiadakis, Tim van Kasteren, Wenzhi Liao, Rik Bellens, Aleksandra Pizurica, Sidharta Gautama, Wilfried Philips, Saurabh Prasad (+2 others)
2014 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
scheme, and a graph-based method for the fusion of spectral, spatial, and elevation information.  ...  This paper highlights the two awarded research contributions, which investigated different approaches for the fusion of hyperspectral and LiDAR data, including a combined unsupervised and supervised classification  ...  ACKNOWLEDGMENTS The authors and IEEE GRSS DFTC would like to express their great appreciation to the Hyperspectral Image Analysis group and the NSF Funded Center for Airborne Laser Mapping (NCALM) at the  ... 
doi:10.1109/jstars.2014.2305441 fatcat:qsisbm7marchxkpjkvxops3nsy

Efficient Morphometric Techniques in Alzheimer's Disease Detection: Survey and Tools

Vinutha N., P. Deepa Shenoy, P. Deepa Shenoy, K.R. Venugopal
2016 Neuroscience International  
The registration techniques like Mutual Information Registration, Fluid registration, Rigid registration, Spatial Transformation algorithm for registration, Elastic Registration are selected based on type  ...  The development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer's Disease (AD) and to prevent the  ...  The corresponding author confirms that all of the other authors have read and approved the manuscript and there are no ethical issues involved.  ... 
doi:10.3844/amjnsp.2016.19.44 fatcat:3zeb2s5pjzfv7mptqi7cy2a3au

International Conference on Image Processing

1996 Proceedings of 3rd IEEE International Conference on Image Processing  
transforms Histogram based fuzzy Kohonen clustering network for image segmentation -Image coding with fuzzy region-growing segmentation Tracking fuzzy storm centers in doppler radar images Unsupervised  ...  Nishikawa"Morphological registration of 3D medical images.Jean-Philippe Thiran, B. Macq, C.  ... 
doi:10.1109/icip.1996.560353 fatcat:le3ysy6wxrfr7nq56ueropy7tu

Proceedings of 3rd IEEE International Conference on Image Processing

1996 Proceedings of 3rd IEEE International Conference on Image Processing ICIP-96  
Nishikawa* Morphological registration of 3D medical images. 253 Jean-Philippe Thiran, B. Macq, C.  ...  transforms Histogram based fuzzy Kohonen clustering network for image segmentation Image coding with fuzzy region-growing segmentation Tracking fuzzy storm centers in doppler radar images Unsupervised  ... 
doi:10.1109/icip.1996.559416 fatcat:jb4cdydgf5edtdljfuzj423ozu

Multimodal Neuroimaging-based Prediction of Adult Outcomes in Childhood-onset ADHD using Ensemble Learning Techniques

Yuyang Luo, Tara L. Alvarez, Jeffrey M. Halperin, Xiaobo Li
2020 NeuroImage: Clinical  
of major white matter fiber tracts, pair-wise regional connectivity and global/nodal topological properties of the functional brain network for cue-evoked attention process.  ...  All currently available optimization strategies for ELTs (i.e., voting, bagging, boosting and stacking techniques) were tested in a pool of semifinal classification results generated by seven basic classifiers  ...  Research (CBIR17PIL012), and the New Jersey Institute of Technology Start-up Award.  ... 
doi:10.1016/j.nicl.2020.102238 pmid:32182578 pmcid:PMC7076568 fatcat:czuo3ptq2fbjlndgtchrizgss4

Bridging Gap between Image Pixels and Semantics via Supervision: A Survey [article]

Jiali Duan, C.-C. Jay Kuo
2022 arXiv   pre-print
Experiences are drawn from two application domains to illustrate this point: 1) object detection and 2) metric learning for content-based image retrieval (CBIR).  ...  The fact that there exists a gap between low-level features and semantic meanings of images, called the semantic gap, is known for decades. Resolution of the semantic gap is a long standing problem.  ...  and classification [153] , point cloud classification and registration [76, 77, [194] [195] [196] , image and texture generation [90, 91], anomaly detection [193] and medical image classification  ... 
arXiv:2107.13757v3 fatcat:dw4c74c3h5bvlmzmxugeh5aela
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