The first step in most computer aided diagnosis systems is an accurate segmentation of breast region, which affects not only the accuracy but also the speed of the analysis because it significantly reduces the area of the image to be examined. The second step usually includes removal of pectoral muscle region, which is seen in mediolateral oblique view mammograms. This is primarily done to reduce the number of false positive breast cancer detections. In this paper, a method for the segmentation of breast region based on contrast enhancement and k-means algorithm is proposed. To extract pectoral muscle, a region of interest is found, its contrast is enhanced and the pectoral muscle is identified using k-means algorithm. Cubic polynomial fitting is used for the estimation of muscle's boundary. The method is validated with mammograms from miniMIAS database.
Enzymatic hydrolysis of food proteins is convenient method to improve their functional properties and physiological activity. Herein, the successful covalent attachment of alcalase on alginate micron and submicron beads using the carbodiimide based chemistry reaction and the subsequent application of the beads for egg white and soy proteins hydrolysis were studied. In addition to the electrostatic extrusion technique (EE) previously used by others, the potential utilization of a novel ultrasonic spray atomization technique without drying (UA) and with drying (UAD) for alginate submicron beads production has been attempted. The immobilization parameters were optimized on microbeads obtained by EE technique (803 ± 23 µm) with respect to enzyme loading and alcalase activity. UA and UAD techniques resulted in much smaller particles (607 ± 103 nm and 394 ± 51 nm in diameter, respectively), enabling even higher enzyme loading of 671.6 ± 4 mg g−1 on the carrier and the highest immobilized alcalase activity of 2716.1 IU g−1 in the standard reaction. The UAD biocatalyst exhibited also better performances in the real food system based on egg white or soy proteins. It has been shown that the immobilized alcalase can be reused in seven successive soy protein hydrolysis cycles with a little decrease in the activity.
Nowadays advantages in face-based modification using DeepFake algorithms made it possible to replace a face of one person with a face of another person. Thus, it is possible to make not only copy-move modifications, but to implement artificial intelligence and deep learning for replacing face movements from one person to another. Still images can be converted into video sequences. Consequently, the contemporaries, historical figures or even animated characters can be lively presented. Deepfakes are becoming more and more successful and it is difficult to detect them in some cases. In this paper we explain the video sequences we produced (e.g. using X2Face method, and First Order Motion Model for Image Animation) and perform deepfake video analysis using SIFT (Scale Invariant Feature Transform) based approach. The experiments show the simplicity in video forgery production, as well as the possible role of SIFT keypoints detection in differentiation between the deeply forged and original video content.
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