A Data Hiding Method Based on Partition Variable Block Size with Exclusive-or Operation on Binary Image

In this paper, we propose a high capacity data hiding method applying in binary images. Since a binary image has only two colors, black or white, it is hard to hide data imperceptible. The capacities and imperception are always in a trade-off problem. Before embedding we shuffle the secret data by a pseudo-random number generator to keep more secure. We divide the host image into several non-overlapping (2n+1) by (2n+1) sub-blocks in an M by N host image as many as possible, where n can equal 1, 2, 3 , …, or min(M,N). Then we partition each sub-block into four overlapping (n+1) by (n+1) sub-blocks. We skip the all blacks or all whites in each (2n+1) by (2n+1) sub-blocks. We consider all four (n+1) by (n+1) sub-blocks to check the XOR between the non overlapping parts and center pixel of the (2n+1) by (2n+1) sub-block, it embed n 2 bits in each (n+1) by (n+1) sub-block, totally are 4*n 2 . The entire host image can be embedded 4×n 2×M/(2n+1)×N/(2n+1) bits. The extraction way is simply to test the XOR between center pixel with their non-overlapping part of each sub-block. All embedding bits are collected and shuffled back to the original order. The adaptive means the partitioning sub-block may affect the capacities and imperception that we want to select. The experimental results show that the method provides the large embedding capacity and keeps imperceptible and reveal the host image lossless

Impact of body-mass factors on setup displacement in patients with head and neck cancer treated with radiotherapy using daily on-line image guidance

BACKGROUND: To determine the impact of body-mass factors (BMF) before radiotherapy and changes during radiotherapy on the magnitude of setup displacement in patients with head and neck cancer (HNC). METHODS: The clinical data of 30 patients with HNC was analyzed using the alignment data from daily on-line on-board imaging from image-guided radiotherapy. BMFs included body weight, body height, and the circumference and bilateral thickness of the neck. Changes in the BMFs during treatment were retrieved from cone beam computed tomography at the 10th and 20th fractions. Setup errors for each patient were assessed by systematic error (SE) and random error (RE) through the superior-inferior (SI), anterior-posterior (AP), and medial-lateral (ML) directions, and couch rotation (CR). Using the median values of the BMFs as a cutoff, the impact of the factors on the magnitude of displacement was assessed by the Mann–Whitney U test. RESULTS: A higher body weight before radiotherapy correlated with a greater AP-SE (p = 0.045), SI-RE (p = 0.023), and CR-SE (p = 0.033). A longer body height was associated with a greater SI-RE (p = 0.002). A performance status score of 1 or 2 was related to a greater AP-SE (p = 0.043), AP-RE (p = 0.015), and SI-RE (p = 0.043). Among the ratios of the BMFs during radiotherapy, the values at the level of mastoid tip at the 20(th) fraction were associated with greater setup errors. CONCLUSIONS: To reduce setup errors in patients with HNC receiving RT, the use of on-line image-guided radiotherapy is recommended for patients with a large body weight or height, and a performance status score of 1–2. In addition, adaptive planning should be considered for those who have a large reduction ratio in the circumference (<1) and thickness (<0.94) over the level of the mastoid tip during the 20(th) fraction of treatment

18F-FDG PET/CT-based gross tumor volume definition for radiotherapy in head and neck Cancer: a correlation study between suitable uptake value threshold and tumor parameters

<p>Abstract</p> <p>Background</p> <p>To define a suitable threshold setting for gross tumor volume (GTV) when using ¹⁸Fluoro-deoxyglucose positron emission tomography and computed tomogram (PET/CT) for radiotherapy planning in head and neck cancer (HNC).</p> <p>Methods</p> <p>Fifteen HNC patients prospectively received PET/CT simulation for their radiation treatment planning. Biological target volume (BTV) was derived from PET/CT-based GTV of the primary tumor. The BTVs were defined as the isodensity volumes when adjusting different percentage of the maximal standardized uptake value (SUVmax), excluding any artifact from surrounding normal tissues. CT-based primary GTV (C-pGTV) that had been previously defined by radiation oncologists was compared with the BTV. Suitable threshold level (sTL) could be determined when BTV value and its morphology using a certain threshold level was observed to be the best fitness of the C-pGTV. Suitable standardized uptake value (sSUV) was calculated as the sTL multiplied by the SUVmax.</p> <p>Results</p> <p>Our result demonstrated no single sTL or sSUV method could achieve an optimized volumetric match with the C-pGTV. The sTL was 13% to 27% (mean, 19%), whereas the sSUV was 1.64 to 3.98 (mean, 2.46). The sTL was inversely correlated with the SUVmax [sTL = -0.1004 Ln (SUVmax) + 0.4464; R²= 0.81]. The sSUV showed a linear correlation with the SUVmax (sSUV = 0.0842 SUVmax + 1.248; R²= 0.89). The sTL was not associated with the value of C-pGTVs.</p> <p>Conclusion</p> <p>In PET/CT-based BTV for HNC, a suitable threshold or SUV level can be established by correlating with SUVmax rather than using a fixed threshold.</p

A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia

Atrial fibrillation (AF) is the most common cardiovascular disease (CVD); and most existing algorithms are usually designed for the diagnosis (i.e.; feature classification) or prediction of AF. Artificial intelligence (AI) algorithms integrate the diagnosis of AF electrocardiogram (ECG) and predict the possibility that AF will occur in the future. In this paper; we utilized the MIT-BIH AF Database (AFDB); which is composed of data from normal people and patients with AF and onset characteristics; and the AFPDB database (i.e.; PAF Prediction Challenge Database); which consists of data from patients with Paroxysmal AF (PAF; the records contain the ECG preceding an episode of PAF); and subjects who do not have documented AF. We extracted the respective characteristics of the databases and used them in modeling diagnosis and prediction. In the aspect of model construction; we regarded diagnosis and prediction as two classification problems; adopted the traditional support vector machine (SVM) algorithm; and combined them. The improved quantum particle swarm optimization support vector machine (IQPSO-SVM) algorithm was used to speed the training time. During the verification process; the clinical FZU-FPH database created by Fuzhou University and Fujian Provincial Hospital was used for hybrid model testing. The data were obtained from the Holter monitor of the hospital and encrypted. We proposed an algorithm for transforming the PDF ECG waveform images of hospital examination reports into digital data. For the diagnosis model and prediction model trained using the training set of the AFDB and AFPDB databases; the sensitivity; specificity; and accuracy measures were 99.2% and 99.2%; 99.2% and 93.3%; and 91.7% and 92.5% for the test set of the AFDB and AFPDB databases; respectively. Moreover; the sensitivity; specificity; and accuracy were 94.2%; 79.7%; and 87.0%; respectively; when tested using the FZU-FPH database with 138 samples of the ECG composed of two labels. The composite classification and prediction model using a new water-fall ensemble method had a total accuracy of approximately 91% for the test set of the FZU-FPH database with 80 samples with 120 segments of ECG with three labels

Taiwan Oscillation Network

The Taiwan Oscillation Network (TON) is a ground-based network to measure solar intensity oscillations to study the internal structure of the Sun. K-line full-disk images of 1000 pixels diameter are taken at a rate of one image per minute. Such data would provide information onp-modes withl as high as 1000. The TON will consist of six identical telescope systems at proper longitudes around the world. Three telescope systems have been installed at Teide Observatory (Tenerife), Huairou Solar Observing Station (near Beijing), and Big Bear Solar Observatory (California). The telescopes at these three sites have been taking data simultaneously since October of 1994. Anl – v diagram derived from 512 images is included to show the quality of the data

A Low Power Fully Integrated Analog Baseband Circuit with Variable Bandwidth for 802.11 a/b/g WLAN

Abstract: This paper presents experimental results of an analog baseband circuit with variable bandwidth for WLAN direct conversion receiver in UMC 0.18um CMOS process. A seventh order chebyshev lowpass filter with triple bandwidth is used in the analog baseband circuit. The bandwidth is selectable from 7.56MHz, 19.5MHz, or 26.5MHz. The circuit adopts the servo loop for dc offset cancellation. It also has a gain range from 20dB to 60 dB with 10 dB steps while only dissipating 22.248mW. In addition, an automatic frequency tuning loop (ATL) is reported to achieve the bandwidth accuracy of the filter