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Books on the topic 'Segmentation des images échographiques'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Gorte, Ben. Probabilistic segmentation of remotely sensed images. International Institute for Aerospace Survey and Earth Sciences (ITC), 1998.

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2

Banik, Shantanu, Rangaraj M. Rangayyan, and Graham S. Boag. Landmarking and Segmentation of 3D CT Images. Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-01635-6.

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3

Zuluaga, Maria A., Kanwal Bhatia, Bernhard Kainz, Mehdi H. Moghari, and Danielle F. Pace, eds. Reconstruction, Segmentation, and Analysis of Medical Images. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52280-7.

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4

Tuckett, Nicholas M. Maximum gradient profile segmentation of gesture images. UMIST, 1995.

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5

Griffiths, Jane Edisbury. Market segmentation and the corporate images of grocery retailers. University of Manchester, 1996.

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6

Zhuang, Xiahai, and Lei Li, eds. Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65651-5.

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7

Anil, Phatak, Chatterji Gano, and Ames Research Center, eds. Scene segmentation of natural images using texture measures and back-propagation. National Aeronautics and Space Administration, Ames Research Center, 1993.

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8

Ma, Jun, Yuyin Zhou, and Bo Wang, eds. Medical Image Segmentation Foundation Models. CVPR 2024 Challenge: Segment Anything in Medical Images on Laptop. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81854-7.

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9

Noltimier, Katy Farness. Geological analysis of ERS-1 SAR mosaic: Implications for the tectonic segmentation of the Antarctic Peninsula. Byrd Polar Research Center, Ohio State University, 1998.

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10

Abkar, Ali Akbar. Likelihood-based segmentation and classification of remotely sensed images: A Bayesian optimization approach for combining RS and GIS. International Institute for Aerospace Survey and Earth Sciences, 1999.

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11

Bloomquist, James D. Hierarchical image segmentation to infrared images. 1985.

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12

Boag, Graham, Rangaraj Rangayyan, and Shantanu Banik. Landmarking and Segmentation of 3D CT Images. Springer International Publishing AG, 2009.

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13

Bhatia, Kanwal, Maria A. Zuluaga, Bernhard Kainz, Mehdi H. Moghari, and Danielle F. Pace. Reconstruction, Segmentation, and Analysis of Medical Images. Springer, 2017.

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14

Boag, Graham, Rangaraj Rangayyan, and Shantanu Banik. Landmarking and Segmentation of 3D CT Images. Morgan & Claypool Publishers, 2009.

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15

Hacipasaoglu, Kani. Segmentation of noisy images using nonstationary Markov fields. 1987.

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16

Kupeli, Timur. Comparison of model-based segmentation algorithms for color images. 1987.

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17

Shafarenko, Leila. Perception-driven automatic segmentation of colour images using mathematical morphology. 1996.

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18

wasson, vikas, and gurinder kaur. Novel Approach for Thyroid Segmentation of Ultrasound Images Based on Neural Networks. Independently Published, 2018.

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19

Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis. AK Peters, 2004.

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20

Pulse Coupled Neural Networks for the Segmentation of Magnetic Resonance Brain Images. Storming Media, 1996.

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21

Galda, Harald. Development of a Segmentation Method for Dermoscopic Images Based on Color Clustering. GRIN Verlag GmbH, 2007.

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22

Evaluation of Segmentation for Bone Structures in 3D Rendering of Ultrasound Residual Limb Images. Storming Media, 1996.

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23

Behrooz, Ali. Systems and Methods for Automated Segmentation of Individual Skeletal Bones in 3D Anatomical Images: United States Patent 9999400. Independently Published, 2020.

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24

Saidane, Zohra. Image and video text recognition using convolutional neural networks: Study of new CNNs architectures for binarization, segmentation and recognition of text images. LAP Lambert Academic Publishing, 2011.

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25

Li, Lei, and Xiahai Zhuang. Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images: First Challenge, MyoPS 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Springer International Publishing AG, 2020.

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26

Rajakumar, P. S., S. Geetha, and T. V. Ananthan. Fundamentals of Image Processing. Jupiter Publications Consortium, 2023. http://dx.doi.org/10.47715/jpc.b.978-93-91303-80-8.

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"Fundamentals of Image Processing" offers a comprehensive exploration of image processing's pivotal techniques, tools, and applications. Beginning with an overview, the book systematically categorizes and explains the multifaceted steps and methodologies inherent to the digital processing of images. The text progresses from basic concepts like sampling and quantization to advanced techniques such as image restoration and feature extraction. Special emphasis is given to algorithms and models crucial to image enhancement, restoration, segmentation, and application. In the initial segments, the i

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27

Schmitt-Beck, Rüdiger, Sigrid Roßteutscher, Harald Schoen, Bernhard Weßels, and Christof Wolf, eds. The Changing German Voter. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198847519.001.0001.

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Over the past half century, the behavior of German voters has changed profoundly—at first rather gradually but during the last decade at accelerated speed. Electoral decision-making has become much more volatile, rendering election outcomes less predictable. Party system fragmentation intensified sharply. The success of the Alternative for Germany (AfD) put an end to Germany’s exceptionality as one of the few European countries without a strong right-wing populist party. Utilizing a wide range of data compiled by the German Longitudinal Election Study, the book examines changing voters’ behavi

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