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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures

Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures

Zheng, Yefeng
Comaniciu, Dorin

Paperback

Medical ReferenceGeneral Computers

ISBN10: 1493955756
ISBN13: 9781493955756
Publisher: Springer Nature
Published: Sep 3 2016
Pages: 268
Weight: 0.90
Height: 0.61 Width: 6.14 Depth: 9.21
Language: English

Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness.

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