General Purpose Medical Image Registration

Medical Image Registration (Biomedical Engineering) by Joseph V. Hajnal  eBooks & eLearning

Posted by tanas.olesya at March 28, 2015
Medical Image Registration (Biomedical Engineering) by Joseph V. Hajnal

Medical Image Registration (Biomedical Engineering) by Joseph V. Hajnal
English | June 27, 2001 | ISBN: 0849300649 | 394 Pages | PDF | 7 MB

Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared.
Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures (repost)

Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures by Yefeng Zheng and Dorin Comaniciu
English | 2014 | ISBN: 1493905996 | 268 pages | PDF | 11,5 MB

Medical Image Understanding and Analysis: 21st Annual Conference  eBooks & eLearning

Posted by Jeembo at Oct. 16, 2017
Medical Image Understanding and Analysis: 21st Annual Conference

Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings by María Valdés Hernández, Víctor González-Castro
English | 2017 | ISBN: 3319609637 | 950 Pages | PDF | 191.1 MB

This book constitutes the refereed proceedings of the 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017, held in Edinburgh, UK, in July 2017.
VipIMAGE 2017: Proceedings of the VI ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing

João Manuel R.S. Tavares, R.M. Natal Jorge, "VipIMAGE 2017: Proceedings of the VI ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing"
English | EPUB | 2017 (2018 Edition) | 1164 Pages | ISBN : 331968194X | 28 MB
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications (repost)

2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications by A. Ardeshir Goshtasby
Wiley-Interscience; 1 edition | March 8, 2005 | English | ISBN: 0471649546 | 284 pages | PDF | 7 MB

To master the fundamentals of image registration, there is no more comprehensive source than 2-D and 3-D Image Registration. In addition to delving into the relevant theories of image registration, the author presents their underlying algorithms. You'll also discover cutting-edge techniques to use in remote sensing, industrial, and medical applications. Examples of image registration are presented throughout, and the companion Web site contains all the images used in the book and provides links to software and algorithms discussed in the text, allowing you to reproduce the results in the text and develop images for your own research needs. 2-D and 3-D Image Registration serves as an excellent textbook for classes in image registration as well as an invaluable working resource.

Medical Image Watermarking: Techniques and Applications  eBooks & eLearning

Posted by AvaxGenius at Aug. 11, 2017
Medical Image Watermarking: Techniques and Applications

Medical Image Watermarking: Techniques and Applications By Amit Kumar Singh, Basant Kumar, Ghanshyam Singh, Anand Mohan
English | PDF | 2017 | 263 Pages | ISBN : 3319576984 | 7.17 MB

This book presents medical image watermarking techniques and algorithms for telemedicine and other emerging applications. This book emphasizes on medical image watermarking to ensure the authenticity of transmitted medical information. It begins with an introduction of digital watermarking, important characteristics, novel applications, different watermarking attacks and standard benchmark tools. This book also covers spatial and transform domain medical image watermarking techniques and their merits and limitations.

Deep Learning and Convolutional Neural Networks for Medical Image Computing  eBooks & eLearning

Posted by ksveta6 at Aug. 11, 2017
Deep Learning and Convolutional Neural Networks for Medical Image Computing

Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (Advances in Computer Vision and Pattern Recognition) by Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang
2017 | ISBN: 3319429981 | English | 326 pages | PDF | 14 MB
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Part II

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II by Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells
English | 2016 | ISBN: 3319467220 | 703 Pages | PDF | 231.6 MB

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Part I

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part I by Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells
English | 2016 | ISBN: 3319467190 | 681 Pages | PDF | 217.2 MB

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016.

Deep Learning and Convolutional Neural Networks for Medical Image Computing  eBooks & eLearning

Posted by AvaxGenius at July 15, 2017
Deep Learning and Convolutional Neural Networks for Medical Image Computing

Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets By Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang
English | PDF | 2017 | 327 Pages | ISBN : 3319429981 | 13.71 MB

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples.