Advances in Image and Data Processing Using VLSI Design. Volume 2 : Biomedical Applications / edited by Sandeep Saini [and three others].

Format:

Book

Contributor:

Saini, Sandeep, editor.

Series:

IOP Ebooks Series

Language:

English

Subjects (All):

Integrated circuits--Very large scale integration.

Integrated circuits.

Physical Description:

1 online resource (276 pages)

Edition:

First edition.

Place of Publication:

Bristol, England : IOP Publishing, [2022]

Summary:

This book provides the frame of design, modeling concepts, and application of Image Processing based systems using VLSI design techniques. This volume focuses on biomedical applications such as cancer detection, ECG, EEG measurements, medical imaging-based healthcare systems and more, helping the research community to get in-depth knowledge of system design with image processing techniques.

Contents:

Intro

Preface

Acknowledgements

Editors&amp

#x02019

biographies

Sandeep Saini

Kusum Lata

Abhishek Sharma

G R Sinha

List of contributors

Chapter 1 Biomedical image signal processing and its VLSI implementation-past, present and future

1.1 Introduction

1.2 Current research trends

1.3 Applications

1.4 Future research direction

1.5 Conclusions

References

Chapter 2 Methodology for real-time processing of medical images, based on GPU architecture

2.1 Introduction

2.2 Materials and methods

2.2.1 Analysis of the characteristics of the images

2.2.2 Search for the best hardware architecture

2.2.3 Search for software for hardware management

2.2.4 Solution proofs of concept

2.2.5 Functional tests with chosen hardware

2.2.6 Solution performance measurement

2.3 Results

2.4 Conclusion

Bibliography

Chapter 3 Genesis of abdominal electrode placements to create a non-invasive FECG database for scientific research

3.1 Introduction

3.1.1 Need for fetal monitoring

3.2 Material and methods

3.2.1 FHR monitoring techniques

3.2.2 Available abdomen database

3.2.3 Abdominal surface electrode configurations

3.3 Results

3.4 Discussion

3.5 Conclusion

Chapter 4 Unsupervised convolutional neural network model for breast cancer detection

4.1 Introduction

4.2 Related work

4.3 Available solutions and proposed methodology

4.3.1 Model development

Chapter 5 Sign language recognition (SLR) system for hearing-impaired people and those with speech disability: a review

5.1 Introduction

5.1.1 Motivation

5.1.2 Sign linguistics

5.2 Data acquisition, feature extraction and classification methods

5.3 Recognition approaches

5.3.1 Approach based on vision

5.3.2 Approach based on sensors.

5.4 SLR feature extraction

5.4.1 Manual feature extraction

5.4.2 Non-manual feature extraction

5.5 Processing and classification methods

5.5.1 Hidden Markov models

5.5.2 Neural network

5.5.3 Other processing and classification approaches

5.6 Conclusion

Chapter 6 Image recognition with speech

6.1 Introduction

6.1.1 Human vision versus computer vision

6.1.2 Computer vision for the visually impaired

6.1.3 Literature survey

6.2 Image classification

6.2.1 Basics of image classification

6.2.2 CNN based image classification

6.2.3 Basic concepts used in CNN

6.2.4 Various CNN based image classification models

6.2.5 Tools//frameworks used

6.3 Speech converter

6.3.1 Google text-to-speech API

6.3.2 pygame

6.4 Implementation

6.4.1 Motive

6.4.2 Basic pipeline of the project

6.5 Program code

6.6 Final result

6.7 Conclusion and future scope

6.7.1 Conclusion

6.7.2 Future scope

Chapter 7 Methodology for the creation and evaluation of a database of medical images: cerebral cysticercosis case

7.1 Introduction

7.2 Materials and methods

7.2.1 Imaging needs analysis

7.2.2 Search for medical images in DICOM format

7.2.3 Image pre-processing

7.2.4 Conversion of images

7.2.5 Features extraction

7.2.6 Order and final disposition

7.3 Results

7.4 Conclusion

Chapter 8 Smart homes: the next urban evolution in smart cities for elderly and disabled people to give a better quality of life

8.1 Introduction

8.1.1 Next urban evolution

8.1.2 Requirements of elderly and disabled people

8.2 Related work

8.3 Available solutions and proposed methodology

References.

Chapter 9 Practical techniques for the fight against COVID-19: using today's technology to make prevention strategy more efficient and effective

9.1 Introduction

9.1.1 Social distancing cap

9.1.2 Automatic sanitizer dispensing system

9.1.3 Automatic doorbell

9.1.4 Automatic temperature sensitive doors

9.1.5 Automatic washbasin

9.1.6 Sanitization tunnel

9.1.7 Low cost ventilators

9.2 Problem definition and proposed solution 'Namaste: Enhanced Safety Technology' (NEST)

9.2.1 Objective of 'Namaste: Enhanced Safety Technology' (NEST)

9.3 User-centred design and ergonomics applied to the proposed solution

9.4 Safe implementation and use of NEST for all users

9.4.1 Design methodology

9.4.2 NEST system functionality test

9.5 Socioeconomic systems and impact of policy decision on use of proposed solution NEST in day-to-day life

9.6 Benefits of using NEST

9.7 Conclusion and future research directions

Chapter 10 Field programmable gate array implementation of MRI image segmentation for brain tumor detection and classification using a deep learning algorithm

10.1 Introduction

10.2 Related work

10.2.1 International scenario

10.2.2 National scenario

10.3 Problem statement

10.4 Implementation methodology

10.4.1 Proposed system description

10.4.2 MRI image segmentation using DCNN

10.4.3 Feature extraction

10.4.4 FPGA implementation methodology

10.4.5 Algorithm flow for the FPGA implementation

10.4.6 Brain tumor classification using multi-class LIB-SVM

10.5 Performance metrics

10.6 Conclusion

Chapter 11 A review on secure image transfer techniques and hardware security

11.1 Introduction

11.2 Image security

11.2.1 Goals of image security

11.3 Hardware security

11.3.1 Hardware vulnerabilities taxonomy.

11.3.2 Hardware attacks taxonomy

11.4 Conclusion

Chapter 12 Design and development of an iOS mobile application with the help of VLSI design

12.1 Introduction

12.1.1 Xcode

12.1.2 Prominent features of Xcode [23]

12.2 IDE (integrated development environment)

12.3 Differences between objective-C and other C languages

12.3.1 Messages

12.3.2 Interfaces and implementations

12.3.3 Dynamic typing

12.3.4 Instantiation

12.3.5 Forwarding

12.3.6 Categories

12.4 Objective-C

12.4.1 Xcode 8.3

12.4.2 Swift [24]

12.4.3 Opting SWIFT for development

12.5 Methodology

12.5.1 Implementation

12.5.2 Slide menu bar

12.5.3 My profile

12.5.4 House of WisDom

12.6 Conclusion

Chapter 13 High level synthesis of fingerprint authentication system

13.1 Introduction to high level synthesis

13.2 Mapping of algorithms to architecture

13.2.1 HDL coders

13.3 Introduction to fingerprint authentication systems

13.3.1 Preprocessing stages

13.3.2 Smoothing

13.3.3 Normalization

13.3.4 Segmentation

13.3.5 Binarization

13.4 Feature extraction

13.4.1 Thinning

13.4.2 Minutiae extraction

13.4.3 Implementation of minutiae extraction using MATLAB

13.5 Template creation

13.6 Authentication

13.6.1 Encryption and decryption algorithms

13.7 Matching algorithm

13.7.1 Implementation of matching algorithm using MATLAB and Vivado

13.8 Conclusion

Chapter 14 An efficient 24×7 patient's vital parameter monitoring framework using machine learning based Internet of Biomedical Things: a comprehensive approach

14.1 Introduction

14.2 Related works

14.3 Proposed work

14.3.1 Wearable scheme

14.3.2 Hardware placement and framework

14.3.3 Software based model with IoBT

14.4 Performance evaluation

14.5 Conclusion.

Bibliography

Chapter 15 FPGA implementation for machine learning based automatic facial emotion recognition system

15.1 Introduction

15.2 Literature review

15.3 Proposed method

15.4 Experimental results

15.5 Conclusion

Chapter 16 Role of reduction techniques in VLSI design

16.1 Introduction

16.2 Types of process variations

16.3 Die-to-die and within die process variations

16.4 Devices affected by process variation and NBTI

16.5 Recommended adaptive body bias (ABB) circuit

16.6 Methodology used

16.6.1 Existing design waveform

16.6.2 Output waveform

16.7 Table of proposed design

16.8 Comparison table

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references.

ISBN:

9780750345941

0750345942

OCLC:

1429740533