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Guest editorial for the IJCARS special issue on MICCAI 2017
2018
International Journal of Computer Assisted Radiology and Surgery
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In closing, we would like to thank all members of the Program Committee as well as the reviewers for their support during the entire MICCAI 2017 and IJCARS Special Issue process. ...
We feel confident that this Special Issue provides an interesting window into this body of work and will entice readers to continue their association with, or join anew the MICCAI community. papers touched ...
doi:10.1007/s11548-018-1847-y
pmid:30120692
fatcat:3mi2zk4ocbdsphcnzr55ppxdpa
Special issue: third MICCAI workshop on bio-imaging and visualization for patient-customized simulations
2020
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
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Special issue: third MICCAI workshop on bio-imaging and visualization for patient-customized simulations Imaging and Visualisation are among the most dynamic and innovative areas of research of the past ...
S Tavares & Shuo Li (2020) Special issue: third MICCAI workshop on bio-imaging and visualization for patient-customized simulations, Computer Methods in Biomechanics and Biomedical Engineering: Imaging ...
doi:10.1080/21681163.2020.1847814
fatcat:ghr6flbizvekplm7osi3rslkuu
Guest editorial of the IJCARS MICCAI 2016 special issue
2017
International Journal of Computer Assisted Radiology and Surgery
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Six of the 18 invited papers made it through the review process for this special issue which we proudly present in the following. ...
The papers that scored best in this process got invitations to special issues in the International Journal of Computer Assisted Radiology and Surgery and Medical Image Analysis. ...
We believe that this special issue provides a representative selection from the various topics covered in MICCAI. We hope that the readers will enjoy this collection of papers. ...
doi:10.1007/s11548-017-1642-1
pmid:28744837
fatcat:xjnolunu7jdpzezk52ix3fylcy
Dataset Growth in Medical Image Analysis Research
2021
Journal of Imaging
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Thereupon, we had issued a forecast for dataset sizes in MICCAI 2019 well before the conference. ...
The median dataset size had grown by 3–10 times from 2011 to 2018, depending on imaging modality. ...
Based on this analysis, we issue predictions regarding dataset sizes in the MICCAI 2020 conference (its analysis is beyond the scope of this research) and the MICCAI 2021 conference, noting that it has ...
doi:10.3390/jimaging7080155
pmid:34460791
fatcat:7b5lu44hbvbd7jmaegmtpdmdiu
Guest Editors' Foreword
2017
Healthcare technology letters
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Sacks and the accompanying Opinion Piece on Mitral Valve Modeling and Simulation appearing in this Special Issue. Dr. ...
Virtual and Augmented Reality Challenges in Clinical Neurosurgery included in this Special Issue. ...
doi:10.1049/htl.2017.0078
pmid:29184653
pmcid:PMC5683192
fatcat:u4npivom2nhe7fied6sarpjz3u
The Liver Tumor Segmentation Benchmark (LiTS)
[article]
2019
arXiv
pre-print
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Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. ...
The submitted algorithms have been tested on 70 undisclosed volumes. ...
The second LiTS benchmark was held on September 14, 2017 in Quebec City, Canada as a MICCAI 2017 workshop. ...
arXiv:1901.04056v1
fatcat:25ekt2znl5adnd5laap4ez6a4y
Fully convolutional neural networks for polyp segmentation in colonoscopy
2017
Medical Imaging 2017: Computer-Aided Diagnosis
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We validate our framework on the 2015 MICCAI polyp detection challenge dataset, surpassing the state-of-the-art in automated polyp detection. ...
Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. ...
To combat this issue, a validation framework was proposed in the 2015 MICCAI sub-challenge on automatic polyp detection. 7 The problem of automatic polyp detection is quite challenging. ...
doi:10.1117/12.2254361
dblp:conf/micad/BrandaoMCCBMDKA17
fatcat:7pgzag3xhraqxfendqdstj3mny
Special Issue on Biomedical Big Data: Understanding, Learning and Applications
2017
IEEE Transactions on Big Data
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Qiang Yang for the support and advice for this special issue. ...
The second part of the special issue contains three articles that focus on the tracking and detection problem of cells in microscopy images. ...
doi:10.1109/tbdata.2017.2772930
fatcat:7bvw2qci6vcltiwtenlcqyvaiu
Guest Editorial Special Issue on Adversarial Learning in Computational Intelligence
2020
IEEE Transactions on Emerging Topics in Computational Intelligence
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Guest Editorial Special Issue on Adversarial Learning in Computational Intelligence
I. ...
Specifically, the special issue is organized as follows. ...
doi:10.1109/tetci.2020.3006295
fatcat:yooqkhmmnrg5jcblgngfmikedi
Editorial for the special issue of "Computational methods for molecular imaging" for computerized medical imaging and graphics
2017
Computerized Medical Imaging and Graphics
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addressed in this special issue. ...
This special issue covers the topics of several classical and emerging molecular imaging modalities such as positron emission tomography (PET) (Lu et al., 2017 , Paul et al., 2017 , Karakatsanis et al ...
doi:10.1016/j.compmedimag.2017.06.006
pmid:28701281
fatcat:lj5xcr47srbxvmkaklizellzzu
Evaluating the effect of multiple sclerosis lesions on automatic brain structure segmentation
2017
NeuroImage: Clinical
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and MICCAI'12). ...
On the other hand, FIRST is more affected when the lesions are overlaid or close to the structure of analysis. ...
These last lesions have a special shape that depends on the morphology of the LV and non-rigid deforming the original lesions allows getting adapted to that structure. ...
doi:10.1016/j.nicl.2017.05.003
pmid:28540179
pmcid:PMC5430150
fatcat:w6tdevhqmjgabjl7ruvridjaj4
Diabetic Foot Ulcers Grand Challenge 2023
[article]
2022
Zenodo
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References [1] Goyal, M., Yap, M.H., Reeves, N.D., Rajbhandari, S. and Spragg, J., 2017, October. Fully convolutional networks for diabetic foot ulcer segmentat [...] ...
In an effort to improve patient care and reduce the strain on healthcare systems, recent research has focused on the creation of detection algorithms that could be used as part of a mobile app that patients ...
Our first two MICCAI challenges (DFUC2020 and DFUC2021) were sponsored by NVIDIA, who provided the prizes for the winning team, so we do not anticipate any issues sourcing prizes for 2023. e) Define the ...
doi:10.5281/zenodo.6362522
fatcat:lzt7iydltne7lkkits2ei5fy7a
Diabetic Foot Ulcers Grand Challenge 2022
[article]
2021
Zenodo
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In 2017 IEEE international conference on systems, man, and cybernetics (SMC) (pp. 618-623). IEEE. [2] Cassidy B. et al., 2020. ...
In an effort to improve patient care and reduce the strain on healthcare systems, recent research has focused on the creation of detection algorithms that could be used as part of a mobile app that patients ...
Our first MICCAI challenge (2020) was sponsored by NVIDIA, who provided the prize for the winning team, so we do not anticipate any issues sourcing prizes for 2022. e) Define the policy for result announcement ...
doi:10.5281/zenodo.6388996
fatcat:jbji5yh4yjbjnf3dhuzr6vqnfm
Neural Network based Whole Heart Segmentation from 3D CT images
2020
International journal of electrical and computer engineering systems
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Evaluation of the proposed approach is performed on CT images from MICCAI 2017 Multi-Modality Whole Heart Segmentation Challenge dataset, delivering in a three-fold cross-validation an average dice coefficient ...
To overcome issues of using small datasets, various data augmentation techniques have been developed. ...
The results were evaluated on the five CT volumes from the MICCAI 2017 Multi-Modality Whole Heart Segmentation challenge. ...
doi:10.32985/ijeces.11.1.3
fatcat:liibn2x7ivfgzipphmbknq4bfy
Multiple Sclerosis Lesion Analysis in Brain Magnetic Resonance Images: Techniques and Clinical Applications
[article]
2022
arXiv
pre-print
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Recently, automated statistical imaging analysis techniques have been proposed to detect and segment MS lesions based on MRI voxel intensity. ...
Traditionally, MS lesions have been manually annotated on 2D MRI slices, a process that is inefficient and prone to inter-/intra-observer errors. ...
CONCLUSION AND FUTURE DIRECTIONS We reviewed recent methodologies for MS lesion segmentation, with a special focus on deep-learning approaches. ...
arXiv:2104.10029v3
fatcat:elds3foafrdc5ireld5wahp5ra
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