MOTIVATION: The principle of Breiman's random forest (RF) is to build and assemble complementary classification trees in a way that maximizes their variability. We propose a new type of random forest that disobeys Breiman's principles and involves building trees with no classification errors in very large quantities. We used a new type of decision tree that uses a neuron at each node as well as an in-innovative half Christmas tree structure. With these new RFs, we developed a score, based on a family of ten new statistical information criteria, called Nguyen information criteria (NICs), to evaluate the predictive qualities of features in three dimensions. RESULTS: The first NIC allowed the Akaike information criterion to be minimized more quickly than data obtained with the Gini index when the features were introduced in a logistic regression model. The selected features based on the NICScore showed a slight advantage compared to the support vector machines-recursive feature elimination (SVM-RFE) method. We demonstrate that the inclusion of artificial neurons in tree nodes allows a large number of classifiers in the same node to be taken into account simultaneously and results in perfect trees without classification errors. AVAILABILITY AND IMPLEMENTATION: The methods used to build the perfect trees in this article were implemented in the 'ROP' R package, archived at https://cran.r-project.org/web/packages/ROP/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In this paper, we propose the first joint watermarking-encryption-compression scheme for the purpose of protecting of medical images. The main originality of this scheme stands on its ability to give access to watermarking-based security services from both encrypted and compressed image bitstreams without having to decrypt or to decompress them, even partially. More clearly, there is no need neither to decrypt the encrypted image bitstream nor to decode the compressed image bitstream in order to extract watermarks. A second contribution is that it combines in a single algorithm the bit substitution watermarking modulation with JPEG-LS and the AES block cipher algorithm in its CBC mode. On their side, decompression, decryption and message extraction are conducted separately. Doing so makes our scheme compliant to the medical image standard DICOM. This scheme allows tracing images and controlling their reliability (i.e. based on proofs of image integrity and authenticity) either from the encrypted domain or from the compressed one. Experiments conducted on broad sets of Retina and ultrasound medical images demonstrate the capability of our system to securely make available a message in both encrypted and compressed domains while minimizing image distortion. Achieved watermarking capacities are large enough to support several watermarking-based security services at the same time.