| 000 | 06942cam a2200565 i 4500 | ||
|---|---|---|---|
| 001 | ocn970041768 | ||
| 003 | OCoLC | ||
| 005 | 20250612155440.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 170126s2017 enk ob 001 0 eng d | ||
| 040 |
_aN$T _beng _erda _epn _cN$T _dIDEBK _dEBLCP _dOPELS _dN$T _dYDX _dOCLCQ _dUAB _dOCLCF _dUMI _dIUL _dSTF _dTOH _dCOO _dOCLCO _dMERER _dOCLCO _dOCLCQ _dOTZ _dOCLCQ _dVT2 _dD6H _dU3W _dCEF _dCHVBK _dKSU _dRRP _dOCLCQ _dOCLCO _dTXM _dOCLCQ _dDEBBG _dAU@ _dUKMGB _dOCLCQ _dWYU _dOCLCO _dOCLCA _dOCLCQ _dOCLCO _dOCLCQ _dOCLCA _dOCLCQ _dS2H _dOCLCO _dLVT _dQGK _dOCLCO _dOCLCQ _dSFB _dOCL _dOCLCQ _dOCLCO _dOCLCL _dSXB _dOCLCQ _dOCLCO |
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_a018231475 _2Uk |
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_a9780128104095 _q(electronic bk.) |
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| 020 |
_a0128104090 _q(electronic bk.) |
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| 020 |
_z9780128104088 _q(print) |
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| 020 | _z0128104082 | ||
| 035 |
_a(OCoLC)970041768 _z(OCoLC)970391734 _z(OCoLC)970614077 _z(OCoLC)970754560 _z(OCoLC)971041198 _z(OCoLC)971079124 _z(OCoLC)971228510 _z(OCoLC)971343951 _z(OCoLC)972237768 _z(OCoLC)976000729 _z(OCoLC)1005837908 _z(OCoLC)1008955639 _z(OCoLC)1066462339 _z(OCoLC)1103277567 _z(OCoLC)1129356277 _z(OCoLC)1153002057 _z(OCoLC)1229554802 _z(OCoLC)1263583969 _z(OCoLC)1294681527 |
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| 050 | 4 | _aRC78.7.D53 | |
| 060 | 4 | _aWN 180 | |
| 072 | 7 |
_aMED _x019000 _2bisacsh |
|
| 082 | 0 | 4 |
_a616.07/54 _223 |
| 245 | 0 | 0 |
_aDeep learning for medical image analysis / _cedited by S. Kevin Zhou, Hayit Greenspan, Dinggang Shen. |
| 264 | 1 |
_aLondon, United Kingdom : _bAcademic Press is an imprint of Elsevier, _c[2017] |
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| 264 | 4 | _c�2017 | |
| 300 | _a1 online resource | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 | _aThe Elsevier and MICCAI Society book series | |
| 505 | 0 | _aFront Cover; Deep Learning for Medical Image Analysis; Copyright; Contents; Contributors; About the Editors; Foreword; Part 1 Introduction; 1 An Introduction to Neural Networks and Deep Learning; 1.1 Introduction; 1.2 Feed-Forward Neural Networks; 1.2.1 Perceptron; 1.2.2 Multi-Layer Neural Network; 1.2.3 Learning in Feed-Forward Neural Networks; 1.3 Convolutional Neural Networks; 1.3.1 Convolution and Pooling Layer; 1.3.2 Computing Gradients; 1.4 Deep Models; 1.4.1 Vanishing Gradient Problem; 1.4.2 Deep Neural Networks; 1.4.3 Deep Generative Models; 1.5 Tricks for Better Learning. | |
| 505 | 8 | _a1.5.1 Rectified Linear Unit (ReLU)1.5.2 Dropout; 1.5.3 Batch Normalization; 1.6 Open-Source Tools for Deep Learning; References; Notes; 2 An Introduction to Deep Convolutional Neural Nets for Computer Vision; 2.1 Introduction; 2.2 Convolutional Neural Networks; 2.2.1 Building Blocks of CNNs; 2.2.2 Depth; 2.2.3 Learning Algorithm; 2.2.4 Tricks to Increase Performance; 2.2.5 Putting It All Together: AlexNet; 2.2.6 Using Pre-Trained CNNs; 2.2.7 Improving AlexNet; 2.3 CNN Flavors; 2.3.1 Region-Based CNNs; 2.3.2 Fully Convolutional Networks; 2.3.3 Multi-Modal Networks; 2.3.4 CNNs with RNNs. | |
| 505 | 8 | _a2.3.5 Hybrid Learning Methods2.4 Software for Deep Learning; References; Part 2 Medical Image Detection and Recognition; 3 Efficient Medical Image Parsing; 3.1 Introduction; 3.2 Background and Motivation; 3.2.1 Object Localization and Segmentation: Challenges; 3.3 Methodology; 3.3.1 Problem Formulation; 3.3.2 Sparse Adaptive Deep Neural Networks; 3.3.3 Marginal Space Deep Learning; 3.3.4 An Artificial Agent for Image Parsing; 3.4 Experiments; 3.4.1 Anatomy Detection and Segmentation in 3D; 3.4.2 Landmark Detection in 2D and 3D; 3.5 Conclusion; Disclaimer; References. | |
| 505 | 8 | _a4 Multi-Instance Multi-Stage Deep Learning for Medical Image Recognition4.1 Introduction; 4.2 Related Work; 4.3 Methodology; 4.3.1 Problem Statement and Framework Overview; 4.3.2 Learning Stage I: Multi-Instance CNN Pre-Train; 4.3.3 Learning Stage II: CNN Boosting; 4.3.4 Run-Time Classification; 4.4 Results; 4.4.1 Image Classification on Synthetic Data; 4.4.2 Body-Part Recognition on CT Slices; 4.5 Discussion and Future Work; References; 5 Automatic Interpretation of Carotid Intima-Media Thickness Videos Using Convolutional Neural Networks; 5.1 Introduction; 5.2 Related Work. | |
| 505 | 8 | _a5.3 CIMT Protocol5.4 Method; 5.4.1 Convolutional Neural Networks (CNNs); 5.4.2 Frame Selection; 5.4.3 ROI Localization; 5.4.4 Intima-Media Thickness Measurement; 5.5 Experiments; 5.5.1 Pre- and Post-Processing for Frame Selection; 5.5.2 Constrained ROI Localization; 5.5.3 Intima-Media Thickness Measurement; 5.5.4 End-to-End CIMT Measurement; 5.6 Discussion; 5.7 Conclusion; Acknowledgement; References; Notes; 6 Deep Cascaded Networks for Sparsely Distributed Object Detection from Medical Images; 6.1 Introduction; 6.2 Method; 6.2.1 Coarse Retrieval Model; 6.2.2 Fine Discrimination Model. | |
| 504 | _aIncludes bibliographical references and index. | ||
| 588 | 0 | _aOnline resource; title from PDF title page (ScienceDirect, viewed February 2, 2017). | |
| 520 |
_a"Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis"-- _cprovided by publisher |
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| 650 | 0 |
_aDiagnostic imaging _xData processing. _933900 |
|
| 650 | 0 |
_aImage analysis. _933901 |
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| 650 | 0 | _aDiagnostic imaging. | |
| 700 | 1 |
_aZhou, S. Kevin, _eeditor. _1https://id.oclc.org/worldcat/entity/E39PCjtBkRx8443g8G9XkBVqDC _933903 |
|
| 700 | 1 |
_aGreenspan, Hayit, _eeditor. _1https://id.oclc.org/worldcat/entity/E39PBJwRWXRmRd4FMcCTMymcfq _933904 |
|
| 700 | 1 |
_aShen, Dinggang, _eeditor. _1https://id.oclc.org/worldcat/entity/E39PBJgMBWvdvCjYtwVYydpByd _933905 |
|
| 758 |
_ihas work: _aDeep learning for medical image analysis (Text) _1https://id.oclc.org/worldcat/entity/E39PCGkcRqvrmKp8QmC9TgWftq _4https://id.oclc.org/worldcat/ontology/hasWork |
||
| 776 | 0 | 8 |
_iPrint version: _tDeep learning for medical image analysis. _dLondon, United Kingdom : Academic Press is an imprint of Elsevier, [2017] _z9780128104088 _z0128104082 _w(OCoLC)957503470 |
| 830 | 0 |
_aElsevier and MICCAI Society book series. _933906 |
|
| 856 | 4 | 0 |
_3ScienceDirect _uhttps://www.sciencedirect.com/science/book/9780128104088 |
| 999 |
_c216378 _d216378 |
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