|
Showing 1 - 6 of
6 matches in All Departments
|
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, …
|
R1,632
Discovery Miles 16 320
|
Ships in 10 - 15 working days
|
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.
|
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, …
|
R1,557
Discovery Miles 15 570
|
Ships in 10 - 15 working days
|
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.
|
Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions - International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011, Proceedings (Paperback)
Anant Madabhushi, Jason Dowling, Henkjan Huisman, Dean Barratt
|
R1,900
Discovery Miles 19 000
|
Ships in 10 - 15 working days
|
This book constitutes the refereed proceedings of the International
Workshop on Prostate Cancer Imaging, held in conjunction with
MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised
full papers presented together with 2 invited talks were carefully
reviewed and selected from 19 submissions. The papers cover the
clinical areas of radiology, radiation oncology, and image guided
intervention, addressing topics such as prostate segmentation,
multi-modal prostate registration, and computer-aided diagnosis and
classification of prostate cancer.
|
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, …
|
R1,557
Discovery Miles 15 570
|
Ships in 10 - 15 working days
|
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.
|
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, …
|
R3,146
Discovery Miles 31 460
|
Ships in 10 - 15 working days
|
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.
Magnetic Resonance (MR) Imaging (MRI), a non-invasive method for
imaging the human body, has revolutionized medical imaging. MR
image processing, particularly segmentation, and analysis are used
extensively in medical and clinical research for advancing our
understanding and diagnosis of various human diseases. These
efforts face two major difficulties - the first due to image
intensity inhomogeneity present as a background variation
component, and the second due to the non-standardness of the MR
image intensities. Scale is a fundamental concept useful in almost
all image processing and analysis tasks. Broadly speaking, scale
related work can be divided into multi-scale representations
(global models) and local scale models. In this thesis, we present
a new morphometric scale model that we refer to as generalized
scale which combines the properties of local scale models with the
global spirit of multi-scale representations. We contend that this
semi-locally adaptive nature of generalized scale confers it
certain distinct advantages over other scale formulations, making
it readily applicable to solving several image processing tasks.
|
You may like...
Poor Things
Emma Stone, Mark Ruffalo, …
DVD
R449
R329
Discovery Miles 3 290
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
Morbius
Jared Leto, Matt Smith, …
DVD
R179
Discovery Miles 1 790
|