Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

Arsalan, Muhammad; Qureshi, Aqsa Saeed; Khan, Asifullah; Rajarajan, Muttukrishnan

doi:10.1016/j.asoc.2016.11.044

Cited by 57 publications

(47 citation statements)

References 29 publications

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“…As the currently international compression standard, JPEG compression is widely used in watermarking [1,2,[7][8][9]. In the watermarking field, many scholars used JPEG attacks [8][9][10]13,14,18,19,21,22]. High-intensity JPEG compression may be applied to watermarking images.…”

Section: Gaussian Noise Attacksmentioning

confidence: 99%

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Liu

et al. 2019

Applied Sciences

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To resolve the contradiction between existing watermarking methods—which are not compatible with the watermark’s ability to resist geometric attacks—and robustness, a robust multi-watermarking algorithm suitable for medical images is proposed. First, the visual feature vector of the medical image was obtained by dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) to perform multi-watermark embedding and extraction. Then, the multi-watermark was preprocessed using the henon map chaotic encryption technology to strengthen the security of watermark information, and combined with the concept of zero watermark to make the watermark able to resist both conventional and geometric attacks. Experimental results show that the proposed algorithm can effectively extract watermark information; it implements zero watermarking and blind extraction. Compared with existing watermark technology, it has good performance in terms of its robustness and resistance to geometric attacks and conventional attacks, especially in geometric attacks.

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Section: Gaussian Noise Attacksmentioning

confidence: 99%

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Liu

et al. 2019

Applied Sciences

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“…Durante los últimos años se han implementado técnicas basadas en marcas de agua, las cuales son aplicadas a imágenes médicas [7][8][9][10][11][12][13]. En la presente sección se presentan los métodos más representativos los cuales aplican técnicas de marcado de agua en imágenes médicas.…”

Section: Estado Del Arteunclassified

“…En [7] se propone una técnica de marca de agua reversible basada en la Transformada de Wavelet Entera (IWT por sus siglas en inglés de Integer Wavelet Transform), este método logra incrustar marcas de agua con baja distorsión, adicionalmente utiliza programación genética (GP) para localizar los coeficientes Wavelet para inserción.…”

Section: Estado Del Arteunclassified

Mejora de un esquema de marca de agua aplicado a la gestión de imágenes médicas

Lagunas¹,

Molina‐García²,

Ponomaryov³

2018

RCS

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En el presente trabajo se propone un método de marca de agua basado en la DWT que aborda los problemas de protección de datos personales y datos sobre los estudios clínicos de un paciente, recuperación de datos del médico que lleva a cabo los estudios y verificación de la integridad de las imágenes médicas. El esquema de marcado realiza la descomposición de una imagen médica en formato DICOM al dominio tiempo-frecuencia mediante la DWT, insertado bits empleados para detección de alteraciones en el primer nivel de descomposición de la sub-banda HL, posteriormente se inserta la información del paciente, identificación del médico e información adicional empleada durante la extracción en la sub-banda de frecuencia LH. Los resultados obtenidos muestran que las imágenes protegidas no se degradan de manera significativa, ya que se obtiene un valor en términos de PSNR (dB) superior a 50dB; asimismo, se demostró que el esquema de marcado de agua es capaz de extraer la información insertada empleando ataques no intencionales como compresión. Finalmente, se mostró experimentalmente la eficiencia del método propuesto para detectar alteraciones empleando ataques de adición de ruido y emborronamiento. Palabras clave: marcas de agua, imágenes médicas, confidencialidad, detección de alteraciones, gestión de imágenes médicas.

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“…Watermarking ensures the protection and authentication of the identity of a person that is embedded into the host audio. Although the use of watermarking in medical images has been extensively studied [26][27][28][29][30], no significant work has been reported for medical speech signals. Only a few studies have been conducted for privacy protection using medical speech signals.…”

Section: Introductionmentioning

confidence: 99%

Chaos-based robust method of zero-watermarking for medical signals

Ali

Imran

Alsulaiman

et al. 2018

Future Generation Computer Systems

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The growing use of wireless health data transmission via Internet of Things is significantly beneficial to the healthcare industry for optimal usage of health-related facilities. However, at the same time, the use raises concerns of privacy protection. Health-related data are private and should be suitably protected. Several pathologies, such as vocal fold disorders, indicate high risks of prevalence in individuals with voice-related occupations, such as teachers, singers, and lawyers. Approximately, one-third of the world population suffer from the voice-related problems during the life span and unauthorized access to their data can create unavoidable circumstances in their personal and professional lives. In this study, a zero-watermarking method is proposed and implemented to protect the identity of patients who suffer from vocal fold disorders. In the proposed method, an image for a patient's identity is generated and inserted into secret keys instead of a host medical signal. Consequently, imperceptibility is naturally achieved. The locations for the insertion of the watermark are determined by a computation of local binary patterns from the timefrequency spectrum. The spectrum is calculated for low frequencies such that it may not be affected by noise attacks. The experimental results suggest that the proposed method has good performance and robustness against noise, and it is reliable in the recovery of an individual's identity.

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Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

Cited by 57 publications

References 29 publications

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Mejora de un esquema de marca de agua aplicado a la gestión de imágenes médicas

Chaos-based robust method of zero-watermarking for medical signals

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