Variational and Level Set Methods in Image Segmentation
Amar Mitiche, Ismail Ben Ayed
Häftad, 2012
1 869 kr
Del i serien The MICCAI Society book Series
1 559 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
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.
Del i serien The MICCAI Society book Series
1 559 kr
Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
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.