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  1. Passive detection of copy-move forgery in digital images: state-of-the-art
    Al-Qershi OM, Khoo BE
    Forensic Sci Int, 2013 Sep 10;231(1-3):284-95.
    PMID: 23890651 DOI: 10.1016/j.forsciint.2013.05.027
    Currently, digital images and videos have high importance because they have become the main carriers of information. However, the relative ease of tampering with images and videos makes their authenticity untrustful. Digital image forensics addresses the problem of the authentication of images or their origins. One main branch of image forensics is passive image forgery detection. Images could be forged using different techniques, and the most common forgery is the copy-move, in which a region of an image is duplicated and placed elsewhere in the same image. Active techniques, such as watermarking, have been proposed to solve the image authenticity problem, but those techniques have limitations because they require human intervention or specially equipped cameras. To overcome these limitations, several passive authentication methods have been proposed. In contrast to active methods, passive methods do not require any previous information about the image, and they take advantage of specific detectable changes that forgeries can bring into the image. In this paper, we describe the current state-of-the-art of passive copy-move forgery detection methods. The key current issues in developing a robust copy-move forgery detector are then identified, and the trends of tackling those issues are addressed.
  2. Fulltext Authentication and data hiding using a hybrid ROI-based watermarking scheme for DICOM images
    Al-Qershi OM, Khoo BE
    J Digit Imaging, 2011 Feb;24(1):114-25.
    PMID: 19937363 DOI: 10.1007/s10278-009-9253-1
    Authenticating medical images using watermarking techniques has become a very popular area of research, and some works in this area have been reported worldwide recently. Besides authentication, many data-hiding techniques have been proposed to conceal patient's data into medical images aiming to reduce the cost needed to store data and the time needed to transmit data when required. In this paper, we present a new hybrid watermarking scheme for DICOM images. In our scheme, two well-known techniques are combined to gain the advantages of both and fulfill the requirements of authentication and data hiding. The scheme divides the images into two parts, the region of interest (ROI) and the region of non-interest (RONI). Patient's data are embedded into ROI using a reversible technique based on difference expansion, while tamper detection and recovery data are embedded into RONI using a robust technique based on discrete wavelet transform. The experimental results show the ability of hiding patient's data with a very good visual quality, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side. The scheme also shows some robustness against certain levels of salt and pepper and cropping noise.
  3. Causal relationships between breast cancer risk factors based on mammographic features
    Ye Z, Nguyen TL, Dite GS, MacInnis RJ, Schmidt DF, Makalic E, et al.
    Breast Cancer Res, 2023 Oct 25;25(1):127.
    PMID: 37880807 DOI: 10.1186/s13058-023-01733-1
    BACKGROUND: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology.

    METHODS: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method.

    RESULTS: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P 

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