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Showing 1 - 9 of
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Deep Learning for Medical Image Analysis, Second Edition is a great
learning resource for academic and industry researchers and
graduate students taking courses on machine learning and deep
learning for computer vision and medical image computing and
analysis. Deep learning provides exciting solutions for medical
image analysis problems and is a key method for future
applications. This book gives a clear understanding of the
principles and methods of neural network and deep learning
concepts, showing how the algorithms that integrate deep learning
as a core component are applied to medical image detection,
segmentation, registration, and computer-aided analysis.
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Multimodal Learning for Clinical Decision Support - 11th International Workshop, ML-CDS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings (Paperback, 1st ed. 2021)
Tanveer Syeda-Mahmood, Xiang Li, Anant Madabhushi, Hayit Greenspan, Quanzheng Li, …
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R1,632
Discovery Miles 16 320
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Ships in 10 - 15 working days
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This book constitutes the refereed joint proceedings of the 11th
International Workshop on Multimodal Learning for Clinical Decision
Support, ML-CDS 2021, held in conjunction with the 24th
International Conference on Medical Imaging and Computer-Assisted
Intervention, MICCAI 2021, in Strasbourg, France, in October 2021.
The workshop was held virtually due to the COVID-19 pandemic.The 10
full papers presented at ML-CDS 2021 were carefully reviewed and
selected from numerous submissions. The ML-CDS papers discuss
machine learning on multimodal data sets for clinical decision
support and treatment planning.
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Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures - 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings (Paperback, 1st ed. 2020)
Tanveer Syeda-Mahmood, Klaus Drechsler, Hayit Greenspan, Anant Madabhushi, Alexandros Karargyris, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the refereed joint proceedings of the 10th
International Workshop on Multimodal Learning for Clinical Decision
Support, ML-CDS 2020, and the 9th International Workshop on
Clinical Image-Based Procedures, CLIP 2020, held in conjunction
with the 23rd International Conference on Medical Imaging and
Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in
October 2020. The workshops were held virtually due to the COVID-19
pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full
papers presented at CLIP 2020 were carefully reviewed and selected
from numerous submissions to ML-CDS and 10 submissions to CLIP. The
ML-CDS papers discuss machine learning on multimodal data sets for
clinical decision support and treatment planning. The CLIP
workshops provides a forum for work centered on specific clinical
applications, including techniques and procedures based on
comprehensive clinical image and other data.
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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support - Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings (Paperback, 1st ed. 2019)
Kenji Suzuki, Mauricio Reyes, Tanveer Syeda-Mahmood, Ender Konukoglu, Ben Glocker, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the refereed joint proceedings of the Second
International Workshop on Interpretability of Machine Intelligence
in Medical Image Computing, iMIMIC 2019, and the 9th International
Workshop on Multimodal Learning for Clinical Decision Support,
ML-CDS 2019, held in conjunction with the 22nd International
Conference on Medical Imaging and Computer-Assisted Intervention,
MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers
presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS
2019 were carefully reviewed and selected from 10 submissions to
iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus
on introducing the challenges and opportunities related to the
topic of interpretability of machine learning systems in the
context of medical imaging and computer assisted intervention. The
ML-CDS papers discuss machine learning on multimodal data sets for
clinical decision support and treatment planning.
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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures - First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings (Paperback, 1st ed. 2019)
Hayit Greenspan, Ryutaro Tanno, Marius Erdt, Tal Arbel, Christian Baumgartner, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the First
International Workshop on Uncertainty for Safe Utilization of
Machine Learning in Medical Imaging, UNSURE 2019, and the 8th
International Workshop on Clinical Image-Based Procedures, CLIP
2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in
October 2019. For UNSURE 2019, 8 papers from 15 submissions were
accepted for publication. They focus on developing awareness and
encouraging research in the field of uncertainty modelling to
enable safe implementation of machine learning tools in the
clinical world. CLIP 2019 accepted 11 papers from the 15
submissions received. The workshops provides a forum for work
centred on specific clinical applications, including techniques and
procedures based on comprehensive clinical image and other data.
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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, Proceedings (Paperback, 1st ed. 2017)
M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, Joao Manuel R.S. Tavares, …
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R3,146
Discovery Miles 31 460
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Ships in 10 - 15 working days
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This book constitutes the refereed joint proceedings of the Third
International Workshop on Deep Learning in Medical Image Analysis,
DLMIA 2017, and the 6th International Workshop on Multimodal
Learning for Clinical Decision Support, ML-CDS 2017, held in
conjunction with the 20th International Conference on Medical
Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec
City, QC, Canada, in September 2017. The 38 full papers presented
at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were
carefully reviewed and selected. The DLMIA papers focus on the
design and use of deep learning methods in medical imaging. The
ML-CDS papers discuss new techniques of multimodal mining/retrieval
and their use in clinical decision support.
Deep learning is providing exciting solutions for medical image
analysis problems and is seen as a key method for future
applications. This book gives a clear understanding of the
principles and methods of neural network and deep learning
concepts, showing how the algorithms that integrate deep learning
as a core component have been applied to medical image detection,
segmentation and registration, and computer-aided analysis, using a
wide variety of application areas. Deep Learning for Medical Image
Analysis is a great learning resource for academic and industry
researchers in medical imaging analysis, and for graduate students
taking courses on machine learning and deep learning for computer
vision and medical image computing and analysis.
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Medical Content-Based Retrieval for Clinical Decision Support - Third MICCAI International Workshop, MCBR-CDS 2012, Nice, France, October 1st, 2012, Revised Selected Papers (Paperback, 2013 ed.)
Hayit Greenspan, Henning Muller, Tanveer Syeda-Mahmood
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R1,429
Discovery Miles 14 290
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the Third MICCAI
Workshop on Medical Content-Based Retrieval for Clinical Decision
Support, MCBR-CBS 2012, held in Nice, France, in October 2012. The
10 revised full papers presented together with 2 invited talks were
carefully reviewed and selected from 15 submissions. The papers are
divided on several topics on image analysis of visual or multimodal
medical data (X-ray, MRI, CT, echo videos, time series data),
machine learning of disease correlations in visual or multimodal
data, algorithms for indexing and retrieval of data from visual or
multimodal medical databases, disease model-building and clinical
decision support systems based on visual or multimodal analysis,
algorithms for medical image retrieval or classification, systems
of retrieval or classification using the ImageCLEF collection.
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Medical Content-Based Retrieval for Clinical Decision Support - Second MICCAI International Workshop, MCBR-CDS 2011, Toronto, Canada, September 22, 2011, Revised Selected Papers (Paperback, 2012)
Henning Mueller, Hayit Greenspan, Tanveer Syeda-Mahmood
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R1,897
Discovery Miles 18 970
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the Second MICCAI
Workshop on Medical Content-Based Retrieval for Clinical Decision
Support, MCBR-CBS 2011, held in Toronto, Canada, in September 2011.
The 11 revised full papers presented together with 2 invited talks
were carefully reviewed and selected from 17 submissions. The
papers are divided on several topics on medical image retrieval
with textual approaches, visual word based approaches, applications
and multidimensional retrieval.
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