Rubber band ligation versus coagulation for the treatment of haemorrhoids: a meta-analysis of randomised controlled trials.

Non-surgical therapies have the advantage of lower postoperative pain and complication rates compared with surgical therapies. Rubber band ligation and coagulation are two kinds of non-surgical therapies. The aim of this study is to compare the clinical outcomes of rubber band ligation and coagulation. A systematic review was conducted to identify randomised clinical trials that compare rubber band ligation and coagulation treatments for haemorrhoids. PubMed and Web of Science were searched, from inception to April 30th,2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Fifty-nine studies were identified. Nine trials met the inclusion criteria. All trials were of moderate methodological quality. No significant difference was found between rubber band ligation and coagulation in terms of efficacy rate, postoperative prolapse rate, recurrence rate and postoperative urine retention rate after treatment. Patients undergoing rubber band ligation had higher postoperative pain rate and lower postoperative bleeding rate than patients undergoing coagulation. The subgroup analysis showed that there was no significant difference between rubber band ligation and infrared coagulation or non-infrared coagulation in terms of efficacy rate, postoperative bleeding and postoperative urine retention rate after treatment. Patients undergoing rubber band ligation had a higher postoperative pain rate than patients undergoing infrared coagulation or non-infrared coagulation. We believe that coagulation for haemorrhoids still has a good future. PROSPERO registration number CRD42022311281.

Splicing forgery localization via noise fingerprint incorporated with CFA configuration.

Noise is the inherent intrinsic fingerprint in digital images and is often used for forgery localization. Most noise-based methods assume that the noise is similar over the whole image and can be considered as white Gaussian noise. However, the noise is different in various regions, which degrade the performance of these noise-based methods. To reduce the impact of impractical assumptions, in this paper, we propose an effective noise fingerprint incorporated with CFA configuration for splicing forgery localization. The noise of interpolated pixels is expected to be suppressed after interpolation, and the relationship between the noise levels of adjacent acquired and interpolated pixels is only related to the interpolation algorithm, which is constant in the original image. We utilize a dual tree wavelet based denoising algorithm to extract the noise from the green channel and compute the standard deviation of the noise for acquired and interpolated pixels, respectively. The noise level of acquired and interpolated pixels are then obtained by the geometric mean of the noise standard deviations. Finally, the ratio of noise levels between acquired and interpolated pixels can be a fingerprint to locate tampered regions. Experiments conducted on publicly available databases demonstrate that the proposed approach outperforms previous methods for detecting splice tampering. Moreover, the proposed method is robust to Gaussian filtering and JPEG compression attacks.

Clinical characteristics and long-term outcomes of hospitalised patients with ischemic colitis with different degrees of haematochezia: a retrospective study.

BACKGROUND: Based on the literature, haematochezia is associated with a benign clinical course of ischaemic colitis. However, most cases in the literature presented mild haematochezia associated with ischaemic colitis. Therefore, we aimed to investigate the impact of different degrees of haematochezia on the clinical outcomes of ischaemic colitis. METHODS: Patients were divided into nonhaematochezia, mild-haematochezia, and severe-haematochezia cohorts stratified by the degree of haematochezia. The clinical characteristics and prognoses were retrospectively reviewed. RESULTS: Haematochezia cohort (n = 89) was associated with a lower rate of severe illness (25% vs. 52%, P = 0.001), lower rate of isolated right colon ischaemia (7% vs. 28%, P = 0.001), lower surgery rates (13% vs. 36%, P = 0.001), and shorter hospital stay (12 vs. 17 days, P < 0.001) compared with nonhaematochezia cohort (n = 50). Severe-haematochezia cohort (n = 11) had a higher frequency of severe illness (73% vs. 18%, P < 0.001), higher surgical intervention rate (55% vs. 6%, P < 0.001), higher nonsurgical complication rate, higher in-hospital mortality (45% vs. 0%, P < 0.001), and longer hospital stay (28 vs. 10 days, P = 0.001), compared with mild-haematochezia cohort (n = 78). Additionally, in-hospital mortality (45% vs. 6%, P = 0.003) and nonsurgical complication rate were higher in the severe-haematochezia than in the nonhaematochezia cohort. However, the three cohorts had comparable prognoses for long-term survival and recurrence. CONCLUSIONS: Mild haematochezia was related to a benign clinical course of ischaemic colitis, while lack of haematochezia or severe haematochezia was associated with worse hospitalisation outcomes.

Forensic human image identification using medical indicators.

Diseases not only bring troubles to people's body functions and mind but also influence the appearances and behaviours of human beings. Similarly, we can analyse the diseases from people's appearances and behaviours and use the personal medical history for human identification. In this article, medical indicators presented in abnormal changes of human appearances and behaviours caused by physiological or psychological diseases were introduced, and were applied in the field of forensic identification of human images, which we called medical forensic identification of human images (mFIHI). The proposed method analysed the people's medical signs by studying the appearance and behaviour characteristics depicted in images or videos, and made a comparative examination between the medical indicators of the questioned human images and the corresponding signs or medical history of suspects. Through a conformity and difference analysis on medical indicators and their indicated diseases, it would provide an important information for human identification from images or videos. A case study was carried out to demonstrate and verify the feasibility of the proposed method of mFIHI, and our results showed that it would be important contents and angles for forensic expert manual examination in forensic human image identification.

Image processing effects on the deep face recognition system.

Face recognition technology has become an important quantitative examination method in the field of forensic identification of human images. However, face image quality affects the recognition performance of face recognition systems. Existing research on the effects of face image denoising and enhancement methods on the face recognition performance are typically based on facial images with manually synthesized noises rather than the noises under natural environmental corruption, and their studied face recognition techniques are limited on the traditional face recognition algorithms rather than state-of-the-art convolutional neural network based face recognition methods. In this work, face image materials from 33 real cases in forensic identification of human images were collected for quantitative analysis of the effects of face image denoising and enhancement methods on the deep face recognition performance of the MXNet system architecture based face recognition system. The results show that face image quality has a significant effect on the recognition performance of the face recognition system, and the image processing techniques can enhance the quality of face images, and then improve the recognition precision of the face recognition system. In addition, the effects of the Gaussian filtering are better than the self-snake model based image enhancement method, which indicates that the image denoising methods are more suitable for performance improvement of the deep face recognition system rather than the image enhancement techniques under the application of the practical cases.

Assessment of signature handwriting evidence via score-based likelihood ratio based on comparative measurement of relevant dynamic features.

This paper extends on previous research on the extraction and statistical analysis on relevant dynamic features (width, grayscale and radian combined with writing sequence information) in forensic handwriting examinations. In this paper, a larger signature database was gathered, including genuine signatures, freehand imitation signatures, random forgeries and tracing imitation signatures, which are often encountered in casework. After applying Principle Component Analysis (PCA) of the variables describing the proximity between specimens, a two-dimensional kernel density estimation was used to describe the variability of within-genuine comparisons and genuine-forgery comparisons. We show that the overlap between the within-genuine comparisons and the genuine-forgery comparisons depends on the imitated writer and on the forger as well. Then, in order to simulate casework conditions, cases were simulated by random sampling based on the collected signature dataset. Three-dimensional normal density estimation was used to estimate the numerator and denominator probability distribution used to compute a likelihood ratio (LR). The comparisons between the performance of the systems in SigComp2011 (based on static features) and the method presented in this paper (based on relevant dynamic features) showed that relevant dynamic features are better than static features in terms of accuracy, false acceptance rate, false rejection rate and calibration of likelihood ratios.