Electronic imaging applications in mobile healthcare
"The integration of mobile technology into healthcare has evolved into an important research area called mHealth. This book presents state-of-art research in mobile imaging technologies and their applications to healthcare. Thirteen chapters by leaders in their fields are divided into four part...
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Bellingham, Washington
SPIE
2016
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| Schriftenreihe: | SPIE Press monograph
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| 245 | 1 | 0 | |a Electronic imaging applications in mobile healthcare |c Jinshan Tang, Sos S. Agaian, and Jindong Tan, editors |
| 264 | 1 | |a Bellingham, Washington |b SPIE |c 2016 | |
| 300 | |a 1 online resource (388 pages) |b illustrations | ||
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| 520 | |a "The integration of mobile technology into healthcare has evolved into an important research area called mHealth. This book presents state-of-art research in mobile imaging technologies and their applications to healthcare. Thirteen chapters by leaders in their fields are divided into four parts: Part I on mobile imaging and enhanced visualization, Part II on security issues in mobile healthcare applications, Part III on human external pulsometers, activity recognition, and tracking using mobile devices, and Part IV on mobile healthcare applications, including skin cancer monitoring with an iPhone using image retrieval techniques, a remote mobile medical imaging system based on mobile devices, and an automatic multiview food classification method for food intake assessment on a smart phone. The editors hope that this book will promote further research in mHealth"-- | ||
| 650 | 4 | |a Imaging systems in medicine | |
| 650 | 4 | |a Wireless communication systems in medical care | |
| 653 | |a Electronic books | ||
| 700 | 1 | |a Tang, Jinshan |4 edt | |
| 700 | 1 | |a Agaian, S. S. |4 edt | |
| 700 | 1 | |a Tan, Jindong |4 edt | |
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Datensatz im Suchindex
| _version_ | 1819583090709757952 |
|---|---|
| adam_text | Titel: Electronic imaging applications in mobile healthcare
Autor: Tang, Jinshan
Jahr: 2016
Contents
Preface xi
List of Contributors xv
Acronyms and Abbreviations xvii
I Mobile Healthcare Image Processing and Enhanced Visualization 3
1 Introduction to Electronic Imaging Applications in Mobile Healthcare 3
Zilong Hu
1.1 Introduction 3
1.2 Electronic Imaging in Mobile Health 5
1.3 Mobile Device Use in Healthcare 5
1.3.1 Some common mobile platforms 5
1.3.2 Key techniques used in mobile electronic imaging 7
1.3.2.1 Auto-focus technology 7
1.3.2.2 Image coding, transmission, and storage 8
1.3.2.3 Image security 8
1.4 Examples of Mobile Healthcare Applications 9
1.5 Future Research Directions 11
1.5.1 Developing algorithms with lower CPU and power
consumption requirements 12
1.5.2 GPU accelerated technology for mobile image analysis 12
References 13
2 A Mobile Image Enhancement Technology for Low-Vision Patients 17
Fahao Qiao and Jinshan Tang
2.1 Introduction 17
2.2 Image Enhancement Algorithm 18
2.2.1 2D discrete wavelet transform 18
2.2.2 Direct contrast enhancement in the wavelet
domain—Tang s algorithm 19
2.3 Implementation on the Mobile Phone 22
2.3.1 Xcode 22
2.3.2 Framework of the system 23
2.4 Experimental Results and Conclusions 23
2.4.1 Enhancement effectiveness of Tang s algorithm 25
v
vi
Contents
2.4.2 Comparison of enhancement effectiveness of two contrast
manipulation schemes 26
2.4.2.1 Selecting the preferred enhancement images 28
2.4.2.2 Perceived image quality 29
References 30
3 Cell Phone Camera Color Medical Imaging via Fast Fourier Transform 33
Artyom M. Grigoryan and Sos S. Agaian
3.1 Introduction 33
3.2 Color Images in the Quaternion Space 35
3.3 Two-Sided 2D Quaternion DFTs 38
3.3.1 Column-row algorithm of the two-sided QDFT 42
3.3.2 Fast algorithms for the 2D QDFT 45
3.3.3 Right-side 2D QDFT 49
3.3.4 Column-row wise calculation of the 2D QDFT 50
3.4 Color and Quaternion Image Tensor Representation 51
3.4.1 Right-side 2D QDFT tensor representation 53
3.5 a-Rooting Image Enhancement with 2D QDFT 60
3.6 Conclusion 63
References 64
4 Color Enhancement and Correction for Camera Cell Phone Medical
Images Using Quaternion Tools 77
Artyom M. Grigoryan and Sos S. Agaian
4.1 Introduction 77
4.2 Quaternion Arithmetic, 2D DFT, and Color Image Processing 81
4.2.1 The quaternion numbers 81
4.2.2 Quaternions and color images 82
4.3 Mapping the 2D DFT in Quaternion Algebra 87
4.3.1 Two-sided 2D QDFT 88
4.4 Transform-based Image Enhancement 91
4.4.1 Gray-level image enhancement measure 91
4.5 Quaternion-Transform-based Image Enhancement 93
4.5.1 New color image quality measure 95
4.5.2 Enhancement of images by colors 98
4.6 Conclusion 104
References 104
5 An Adapted Retinex Algorithm with Complexity Optimization for Mobile
Phone Medicallmage Enhancement 119
Artyom M. Grigoryan and Sos S. Agaian
5.1 Introduction 119
5.2 Retinex Algorithms 121
5.2.1 Single-scale retinex method 122
5.2.2 Multiscale retinex method 124
Contents
vii
5.2.3 Multiscale retinex color restoration method 129
5.3 Fast Fourier Transform Multiscale Retinex 130
5.4 FFT-based Image Enhancement: a-Rooting 134
5.5 Script of the FFT-Multiscale Retinex 137
5.6 Conclusion 142
References 142
II Security Issues in Mobile Healthcare Applications 153
6 Secure Medical Image Processing for Mobile Devices Using
Cloud Services 155
Xiaohui Yuan and Mahadevan Gomathisankaran
6.1 Introduction 155
6.2 Background and Related Work 156
6.3 Homomorphic RNS Encryption 157
6.3.1 Semi-perfect secrecy 160
6.3.2 Modulus confidentiality 161
6.3.3 Montgomery representation variations 163
6.3.4 Overflow and sign detection 164
6.4 Secure Image Processing 165
6.5 Experimental Results 167
6.5.1 Implementation and experimental design 167
6.5.2 Results and discussion 168
6.6 Conclusion 171
References 171
7 Cell Phone Medical Image Encryption Based on a Method of
3D Spirals 175
Artyom M. Grigoryan and Bryan Wiatrek
7.1 Introduction 175
7.1.1 Modern cryptography 176
7.2 Digital Images and Traditional Modern Image Cryptography 179
7.3 Nontraditional Modern Image Cryptography 181
7.4 Image, Tensor Representation, and Fourier Transform 190
7.5 Decomposition by Directional Images 195
7.6 Tensor Transform in Image Cryptography 201
7.7 Image Encryption 207
7.7.1 Block diagram of encryption 212
7.7.2 Complexity: The number of keys 212
7.7.2.1 Computation time 215
7.7.2.2 2D DFT of the encryption 215
7.7.2.3 Correlation of adjacent pixels in the
encrypted image 216
7.7.2.4 Image decryption 217
7.7.2.5 Image encryption in the general case of NxM 217
viii
Contents
7.8 Encryption of Color Images 223
7.9 Conclusion 225
References 225
III Human External Pulsometers and Activity Recognition Using
Mobile Devices 233
8 Human Activity Recognition and Processing for Mobile Applications 235
Jafet Morales, Sahak Kaghyan, David Akopian, and Sos S. Agaian
8.1 Introduction 236
8.2 External Environmental and Video-Sensor-based Approaches
for Activity Classification 238
8.3 Wearable Sensors and Mobile Devices as an Approach for
Activity Classification 239
8.3.1 Mobile device positioning technologies used for activity
estimation 240
8.3.2 Wearable inertial sensors 241
8.3.3 Using mobile devices and their sensors used for activity
classification 243
8.3.4 Strengths and weaknesses of mobile-sensor-based
activity classification 244
8.3.5 Activity recognition algorithms and platforms for
smartphone-based activity recognition 245
8.4 Splitting Activity Recognition Tasks for Mobile Computing 246
8.4.1 Multithreading layered mobile computing 246
8.5 Advanced Algorithms for Activity Classification
by Mobile Devices 251
8.5.1 Orientation-invariant motion signals 253
8.5.2 Feature extraction 257
8.5.3 Classification methods 258
8.6 Testing of Algorithms 259
8.7 Concluding Remarks 261
References 262
9 An Improved Smartphone Heart Rate Acquisition System 271
Gevorg Karapetyan, Rafayel Barseghyan, Hakob Sarukhanyan,
and Sos S. Agaian
9.1 Introduction 271
9.1.1 Background 274
9.1.2 Mobile health market 276
9.1.3 HR measurement via mobile phone camera with a
finger over the camera 278
9.2 Improved Remote HR Acquisition System 279
9.3 Experimentation and Validation of the Improved Smartphone HR
Acquisition System 281
Contents
ix
9.3.1 Indoor measurement experiments 282
9.3.2 Outdoor measurement experiments 283
9.3.3 Measuring HR changes during anger and happiness
via mobile device 285
9.4 Implementation on Mobile a Device 285
9.4.1 Computer simulations 286
9.5 Concluding Remarks 289
Acknowledgments 289
References 289
IV Mobile Healthcare Applications 295
10 An iPhone Application for Skin Cancer Monitoring 297
Yanliang Gu and Jinshan Tang
10.1 Introduction 297
10.2 Development Environment 299
10.3 Skin Cancer Image Retrieval Using Boundary Information 300
10.3.1 Introduction to image retrieval 300
10.3.2 Feature extraction using a Fourier descriptor 301
10.3.3 Similarity metric 301
10.4 System Description 301
10.4.1 Flowchart for the iPhone application prototype 301
10.4.2 User interface for iPhone application 303
10.5 Experimental Results 304
10.6 Conclusion 306
References 306
11 A Mobile Healthcare Interface 309
Wei Hu, Daikun Zou, Kai Zhang, Jun Liu, and Xiaoming Liu
11.1 Introduction 309
11.2 Background 311
11.3 System Architecture Model 313
11.3.1 System design 315
11.4 Module Design 316
11.4.1 Module design for the doctor s end 316
11.4.2 Module design for the nurse s end 318
11.4.3 Module design for the data access interface 320
11.5 Fast Medical Image Processing Approach on a Mobile Device 321
11.6 Implementation 323
11.6.1 Hardware description 323
11.6.1.1 Hardware description of the doctor s end 323
11.6.1.2 Hardware description of the nurse s end 323
11.6.2 Implementation of system functions 324
11.6.2.1 Implementation of the doctor s end 324
11.6.2.2 Implementation of the nurse s end 328
X
Contents
11.7 Conclusions 335
References 335
12 DietCam: Multiview Regular-Shaped Food Recognition with a
Camera Phone 339
Fanyu Kong, Hongsheng He, Hollie A. Raynor, and Jindong Tan
12.1 Introduction 339
12.2 Related Work 342
12.3 Multiview Food Recognition 345
12.3.1 Food features 345
12.3.2 Camera calibration 347
12.3.3 Perspective distance 348
12.3.4 Multiview representation 349
12.4 Implementation 353
12.5 Experiment 353
12.5.1 Dataset 354
12.5.2 Baseline methods 354
12.5.3 Segmentation results 355
12.5.4 Classification results 356
12.6 Discussion 360
12.7 Conclusion 360
References 361
Index 365
|
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| discipline | Medizin |
| doi_str_mv | 10.1117/3.2204748 |
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| id | DE-604.BV044242043 |
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| indexdate | 2024-12-24T05:54:49Z |
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| spellingShingle | Electronic imaging applications in mobile healthcare Imaging systems in medicine Wireless communication systems in medical care |
| title | Electronic imaging applications in mobile healthcare |
| title_auth | Electronic imaging applications in mobile healthcare |
| title_exact_search | Electronic imaging applications in mobile healthcare |
| title_full | Electronic imaging applications in mobile healthcare Jinshan Tang, Sos S. Agaian, and Jindong Tan, editors |
| title_fullStr | Electronic imaging applications in mobile healthcare Jinshan Tang, Sos S. Agaian, and Jindong Tan, editors |
| title_full_unstemmed | Electronic imaging applications in mobile healthcare Jinshan Tang, Sos S. Agaian, and Jindong Tan, editors |
| title_short | Electronic imaging applications in mobile healthcare |
| title_sort | electronic imaging applications in mobile healthcare |
| topic | Imaging systems in medicine Wireless communication systems in medical care |
| topic_facet | Imaging systems in medicine Wireless communication systems in medical care |
| url | https://doi.org/10.1117/3.2204748 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029647370&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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