Less-supervised Segmentation with CNNs: Scenarios, Models and
Optimization reviews recent progress in deep learning for image
segmentation under scenarios with limited supervision, with a focus
on medical imaging. The book presents main approaches and
state-of-the-art models and includes a broad array of applications
in medical image segmentation, including healthcare, oncology,
cardiology and neuroimaging. A key objective is to make this
mathematical subject accessible to a broad engineering and
computing audience by using a large number of intuitive graphical
illustrations. The emphasis is on giving conceptual understanding
of the methods to foster easier learning. This book is highly
suitable for researchers and graduate students in computer vision,
machine learning and medical imaging.
General
| Imprint: |
Academic Press Inc
|
| Country of origin: |
United Kingdom |
| Series: |
The MICCAI Society book Series |
| Release date: |
December 2023 |
| First published: |
2024 |
| Editors: |
Jose Dolz
• Ismail Ben Ayed
• Christian Desrosiers
|
| Dimensions: |
234 x 191mm (L x W) |
| Format: |
Paperback
|
| Pages: |
275 |
| ISBN-13: |
978-0-323-95674-1 |
| Categories: |
Books
Promotions
|
| LSN: |
0-323-95674-2 |
| Barcode: |
9780323956741 |
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