Protection of Medical Images and Patient

Related Information Using an Intelligent

Reversible Watermarking Technique

Dr. Asifullah Khan,

Associate Professor, PIEAS

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Medical Image Modalities

• X-ray, MRI, Ultra-Sound, and CT Images

MRI Image

Ultrasound

Image

X-Ray Image

Medical images if not protected can

be manipulated easily

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Illicit Manipulations of Medical Images

• Why tampering of medical images:

Animosity; Rivalry, etc.

Aim may be to mislead Physicians or Forensics experts.

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Image Authenticity

Is this image authentic

and not manipulated ??

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Layout

• Aims and Applications

• Why Protection of Medical Images

• Basics of Watermarking

• Recent Interesting Applications of Watermarking

• Reversible Watermarking

• Proposed Reversible and Intelligent Watermarking

Technique for Medical Images

• Experimental Results

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Aim And Applications

• Aim:

Protecting Medical Images

Secure Access to EPR

• Potential Applications:

Telediagnosis, Teleradiology, and Telesurgery

Invisible hiding of metadata.

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Why we need to Protect Medical Images?

• A large number of images are generated daily in

hospitals, clinics, and laboratories.

• Images need to be stored and communicated.

• However, with the advent of sophisticated image

processing tools, illicit manipulations can be done that

may go un-notice.

• Therefore, medical images need to be protected against

illicit manipulations, forgery attempts, etc.

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Electronic Patient Record ( EPR )

• EPR

– to provide access to a patient's medical records

• It mainly contains patient health information:

medical histories, diagnoses, medications, allergies, lab and

test results ,etc.

• e.g.,

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Advantages of Watermarking Medical Images

Two important things related to Patient: Images and

EPR

Watermarking can thus perform:

Tamper Detection in Medical Images

Secret sharing of medical information (such as EPR)

without losing semantics

EPR can be used as a watermark

– Protects both image and EPR

– Provides limited access to EPR

– Reducing storage & Communication burden

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Basics of Watermarking

• Digital Watermarking

Aim is to secure digital content ( image, audio, video, text,

database, etc.)

Is the practice of invisibly altering an image to embed a

message.

The watermark embedded within the related image may

survive normal image processing operations.

• Cryptography

Is a popular and mature approach to secure digital content.

We loose the semantics of the digital content, when it is

encrypted.

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General Watermarking System

Extraction

function

M(L)

Channel

Retrieved information

Key

Original

work

Information to be embedded

Embedding

function

^ M(L)

Extraction

function

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Watermarking Properties

Imperceptibility

Watermark should be statistically and visually

imperceptible without the compromise on the quality of

data.

Capacity

The maximum size of the message that can be embedded

by the watermarking scheme

Robustness

Watermark should be resistant to the common signal

processing techniques, geometrical distortions and to

forgery attacks.

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Image Watermarking Example

Original Image Watermarked Image

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Applications of Watermarking

• Broadcast Monitoring

• Ownership Assertion

• Content Authentication

• Digital Media Management

• Fingerprinting

• Securing Text and Databases, etc.,

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Recent Interesting Applications of Watermarking

DNA Watermarking

Medicine Authentication using Watermarking and

Smartphones.

Secure Digital Camera

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DNA Watermarking

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Hides Data inside the nucleotide sequence of DNA

Medicine Authentication Using Watermarking

• Easy to imitate the original packaging of a product

becomes a difficult task to identify between the genuine and

fake medicines

• Pharmaceutical companies are one of the major victims of

forgery

not only result in profit loss for the company but the health of

people goes at stack

Authenticating Medicine

Extract Watermark

Internet

Legitimate

Medicine

Fake Medicine

Secure Digital Camera (By Fridrich et. al)

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Reversible Watermarking

• Reversible Watermarking:

Basic reversible image watermarking scheme

Host Image

Secret Information

Restored Image

Secret Information

Watermarked Image

Embedding of Secret

Information

Extraction and

Recovery

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Reversible Watermarking

• Examples of Reversible Watermarking of Images

Original Image Watermarked Image Difference of Original and

Watermarked Image

Restored Image Difference of Original and

Restored Image

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Suitable for

Medical and

Military

applications

Medical Image Watermarking

Basic requirements while protecting Medical Images

Confidentiality

Ensures that only the entitled users have access to the

information.

Reliability

A proof that the information belongs to the correct patient

and issued from the right source

Availability

Warrants an information system to be used in the normal

scheduled conditions of access

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IRW-Med; Intelligent and Reversible Watermarking

Technique

• Learning capabilities of GP are exploited to evolve

models for making an optimal tradeoff between

watermark imperceptibility and capacity.

• This is performed by exploiting the hidden

dependencies of wavelet coefficients and the type of

subbands.

• IRW-Med is able to develop a model that not only

selects suitable wavelet coefficients for embedding, but

also acts a companding factor for the companding

based watermark embedding.

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IRW-Med: Intelligent and Reversible Watermarking

Technique

Reversible Image Watermarking:

Histogram Modification

To avoid underflow and Overflow of Pixel values

Integer wavelet transform

for better exploitation of image content and to ensure

reversibility

Data embedding using companding process

to reduce distortion

GP based Optimization

Optimal tradeoff between watermark Imperceptibility

and capacity

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Basic Block Diagram of IRW-Med

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Pre-Processing

IWT Decomposition

Block Processing

GP Expression (µ)

Watermark Embedding Through Companding

Blocks Merging

Inverse IWT

Payload

EPR

IWT characteristics

Block characteristics

Bookkeeping Data

µ

µ information

Original image

Watermarked image

Previous Prescription etc

Training and Testing phases of IRW-Med

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Watermark

Embedder

Fitness

CalculationImage

Population of candidates

Fitness

Generation

Iterate till population size

Best Individual

Iterate till no. of generation

Training Phase

Watermark

Embedder

Watermark

ExtractorImages

Testing Phase

Results

Save the best

expression

Histogram modification; IRW-Med

2 4 255 70 255 98

3 187 5 3 90 1

3 200 255 67 254 243

0 2 2 87 233 234

0 1 3 99 255 233

0 3 177 101 3 2

0

3

1

2

255

3

254

2

253

2

2

4

0

3

1

6

255

3

254

4

253 2

0 0

2 4 254 70 254 98

3 187 5 3 90 2

3 200 254 67 253 243

1 2 2 87 233 234

1 2 3 99 254 233

1 3 177 101 3 2

Original image Modification image

The BDS is generated (Bookkeeping Data Store)

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Histogram modification; IRW-Med

Bookkeeping data is generated using generated scan

sequence.

BDS=[Total book keeping bit length + compressed number of

grayscales + first histogram from left hand side grayscales + record

length + scan sequence + first histogram from right hand side grayscale +

record length + scan sequence]

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Integer wavelet transform; IRW-Med

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Experimental Results; IRW-Med

• The best expression obtained for lena image is:

plus(times(minus(minus(mylog(mylog(0.27033)),mylog(

kozadivide(blk_index,0.31993))),sin(mylog(blk_index))),

minus(sin(kozadivide(times(0.52962,max_blk),max_blk))

,sin(blk_index))),mean_blk)

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Experimental Results (Performance comparisons)

Capacity vs performance comparisons with existing techniques for Lena image

0.1 0.2 0.3 0.4 0.5 0.6 0.7

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Payload (bpp)

PS

NR

(dB

)

Difference Expension

Xuan Approach GA-RevWM

Spread Spectrum

Bit Plane

Usman et al.

Lee et al.

IWT-Med

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Experimental Results (SSIM based comparisons)

SSIM Comparisons of proposed IWT-Med technique with that of Xuan et al. [11] approach, against different values of

payload.

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Experimental Results (PSNR based comparisons)

PSNR Comparisons of proposed IWT-Med technique with that of Xuan et al. [11] approach, against different values of

payload.

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Authentication Medical Images

(a) Host Image (b) Watermarked Image (c) a - b (d) Restored Image (e) a - d

EPR as a Watermark: Extracted EPR

(a) Host Image (b) Watermarked Image (c) Noisy watermarked image

No Extraction

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Related Publications

• I. Usman, and A. Khan, BCH coding and intelligent watermark embedding:

employing both frequency and strength selection, Applied Soft Computing

Journal vol. 10 (1), pp. 332-343, 2010.

• M. Arsalan, S. A. Malik, and A. Khan, Intelligent Reversible Watermarking in

Integer Wavelet Domain for Medical Images, Journal of Systems and Software,

Vol. 85 (4), pp. 883–894, 2012.

• P Blythe, J Fridrich, Secure Digital Camera, In proceedings of Digital Forensic

Research Workshop, 2004.

• I. Hafiz, A. Khan, A. Qadir, DNA-LCEB: A High Capacity and Mutation

Resistant DNA Data-Hiding Approach by Employing Hybrid 2- and 4-Fold

Codons based Strategy for Synonymous Substitution in Amino Acids, accepted

in Medical & Biological Engineering & Computing, Vol. 52(11), pp. 945-961,

2014.

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Thanks

Special thanks to City University, London

and

Prof. M. Rajarajan

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