Artificial Intelligence in Breast Cancer Early Detection and Diagnosis
By: Khalid Shaikh, Rohit Thanki, Sabitha K
https://www.springer.com/gp/book/9783030592073
This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening. It then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer.
- Discusses various existing screening methods for breast cancer;
- Presents deep information on artificial intelligence-based screening methods;
- Discusses cancer treatment based on geographical differences and cultural characteristics.
Hybrid and Advanced Compression Techniques for Medical Images
By: Rohit Thanki, Ashish Kothari
https://www.springer.com/gp/book/9783030125745
This book introduces advanced and hybrid compression techniques specifically used for medical images. The book discusses conventional compression and compressive sensing (CS) theory based approaches that are designed and implemented using various image transforms, such as: Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Singular Value Decomposition (SVD) and greedy based recovery algorithm. The authors show how these techniques provide simulation results of various compression techniques for different types of medical images, such as MRI, CT, US, and x-ray images. Future research directions are provided for medical imaging science. The book will be a welcomed reference for engineers, clinicians, and research students working with medical image compression in the biomedical imaging field.
- Covers various algorithms for data compression and medical image compression;
- Provides simulation results of compression algorithms for different types of medical images;
- Provides study of compressive sensing theory for compression of medical images.
Dental Image Processing for Human Identification
By: Trivedi, D.N., Shah, N.D., Kothari, A.M., Thanki R.M.
https://www.springer.com/gp/book/9783319994703
This book presents an approach to postmortem human identification using dental image processing based on dental features and characteristics, and provides information on various identification systems based on dental features using image processing operations. The book also provides information on a novel human identification approach that uses Infinite Symmetric Exponential Filter (ISEF) based edge detection and contouring algorithms.
- Provides complete details on dental imaging;
- Discusses the important features of a human identification approach and presents a brief review on DICOM standard for dental imaging;
- Presents human identification approach based on dental features.
Medical Imaging and its Security in Telemedicine Applications
By: Rohit Thanki, Surekha Borra
https://www.springer.com/gp/book/9783319933108
This book introduces medical imaging, its security requirements, and various security mechanisms using data hiding approaches. The book in particular provides medical data hiding techniques using various advanced image transforms and encryption methods. The book focuses on two types of data hiding techniques: steganography and watermarking for medical images. The authors show how these techniques are used for security and integrity verification of medical images and designed for various types of medical images such as grayscale image and color image. The implementation of techniques are done using discrete cosine transform (DCT), discrete wavelet transform (DWT), singular value decomposition (SVD), redundant DWT (RDWT), fast discrete curvelet transform (FDCuT), finite ridgelet transform (FRT) and non-subsampled contourlet transform (NSCT). The results of these techniques are also demonstrated after description of each technique. Finally, some future research directions are provided for security of medical images in telemedicine application.
A steganographic approach for secure communication of medical images based on the DCT-SVD and the compressed sensing (CS) theory
By: Rohit Thanki, Surekha Borra, Vedvyas Dwivedi, Komal Borisaga
https://www.tandfonline.com/doi/abs/10.1080/13682199.2017.1367129
In this paper, a hybrid approach based on cryptography and steganography is proposed for the security of medical image over an open communication channel. In this approach, medical image information is embedded using discrete cosine transform (DCT)-singular value decomposition (SVD)-based embedding process. The medical image is encrypted using CS encryption before embedding into the standard image. This encrypted medical image is inserted into the singular values of DCT coefficients of the standard image to get the stego image. The experimental results show that the encrypted medical image is successfully extracted from the stego image under various image processing attacks at recovering side. The result analysis also shows improved imperceptibility of the stego image with a peak signal-to-noise ratio value above 60 dB for all types of medical images under consideration. Furthermore, the computation time of proposed approach is less than that of existing approaches.