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Roček A, Slavíček K, Dostál O, Javorník M. A new approach to fully-reversible watermarking in medical imaging with breakthrough visibility parameters. Biomed Signal Process Control 2016. [DOI: 10.1016/j.bspc.2016.05.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Duan Y, Bouslimi D, Yang G, Shu H, Coatrieux G. Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints. IEEE J Biomed Health Inform 2016; 21:1039-1048. [PMID: 27295695 DOI: 10.1109/jbhi.2016.2575398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.
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Dey N, Bose S, Das A, Chaudhuri SS, Saba L, Shafique S, Nicolaides A, Suri JS. Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine. J Med Syst 2016; 40:91. [PMID: 26860914 DOI: 10.1007/s10916-016-0451-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 01/29/2016] [Indexed: 11/29/2022]
Abstract
Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.
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Affiliation(s)
- Nilanjan Dey
- Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India.,Department of Information Technology, Techno India College of Technology, Kolkata, India.,Point of Care Devices, Global Biomedical Technologies, Inc, Roseville, CA, USA
| | - Soumyo Bose
- Department of Information Technology, Techno India College of Technology, Kolkata, India
| | - Achintya Das
- Department of ECE, Kalyani Government Engineering College, Bengal, India
| | - Sheli Sinha Chaudhuri
- Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India
| | - Luca Saba
- Radiology Department, zienda Ospedaliero Universitaria (A.O.U.) di Cagliari, Via Roma, 67, 56126, Pisa, PI, Italy
| | - Shoaib Shafique
- CorVasc Vascular Laboratory, 8433 Harcourt Rd #100, Indianapolis, IN, USA
| | - Andrew Nicolaides
- Vascular Screening and Diagnostic Centre, London, UK.,Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus
| | - Jasjit S Suri
- Point of Care Devices, Global Biomedical Technologies, Inc, Roseville, CA, USA. .,Diagnostic and Monitoring Division, AtheroPoint™ LLC, Roseville, CA, USA. .,Electrical Engineering Department (Affl.), Idaho State University, 921 S 8th Ave, Pocatello, ID, 83201, USA.
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