Performance of Machine Learning Classification in Mammography Images using BI-RADS

This research aims to investigate the classification accuracy of various state-of-the-art image classification models across different categories of breast ultrasound images, as defined by the Breast Imaging Reporting and Data System (BI-RADS). To achieve this, we have utilized a comprehensively assembled dataset of 2,945 mammographic images sourced from 1,540 patients. In order to conduct a thorough analysis, we employed six advanced classification architectures, including VGG19 \cite{simonyan2014very}, ResNet50 \cite{he2016deep}, GoogleNet \cite{szegedy2015going}, ConvNext \cite{liu2022convnet}, EfficientNet \cite{tan2019efficientnet}, and Vision Transformers (ViT) \cite{dosovitskiy2020image}, instead of traditional machine learning models. We evaluate models in three different settings: full fine-tuning, linear evaluation and training from scratch. Our findings demonstrate the effectiveness and capability of our Computer-Aided Diagnosis (CAD) system, with a remarkable accuracy of 76.39\% and an F1 score of 67.94\% in the full fine-tuning setting. Our findings indicate the potential for enhanced diagnostic accuracy in the field of breast imaging, providing a solid foundation for future endeavors aiming to improve the precision and reliability of CAD systems in medical imaging

Estimation of speed distribution of particles moving in an optically turbid multiple scattering medium by decomposition of laser-Doppler spectrum

International audienceA novel method for estimation of speed distribution of particles moving in an optically turbid multiple scattering medium by decomposition of laser-Doppler spectrum is presented. In the proposed method Doppler shift probability distributions (DSPD) are utilized. These distributions depend only on anisotropy of medium under investigation. An analytical form of DSPD was proposed which allows to avoid much slower DSPD generation with the use of Monte Carlo code. Method of analytical calculation of DSPDs and laser-Doppler spectra are validated by comparison with results of Monte Carlo simulations. Decomposition of the laser-Doppler spectrum is based on solution of a system of linear equations with constraints. In case of multiple Doppler scattering the decomposition is difficult because of strong dependence of DSPDs generated for various combinations of speeds and number of scattering events. We proposed an approximation based on analysis of multiple Doppler scattering events which occur on particles moving with the same speeds. It was shown that the approximated model gives good results and can be used for analysis of laser-Doppler spectra. The solution of the system of linear equation is based on interior point method, which allows to transform system of linear equations with constraints to minimization problem without constraints using logarithmic barrier functions. The proposed decomposition procedure was verified for different speed distributions with spectra generated by superposition of DSPDs obtained by analytical forms and by use of Monte Carlo simulations

Prevalence of cognitive impairment in peritoneal dialysis patients and associated factors

Background. Cognitive impairment (CI) in patients with chronic kidney disease, including those treated with renal replacement therapy (RRT) is a growing problem worldwide. The study aimed to assess the prevalence of CI and associated factors in patients undergoing peritoneal dialysis (PD). Methods. In this cross-sectional study, 18 consecutive patients with PD therapy and 15 controls were evaluated for CI using the Addenbrooke's Cognitive Examination III (ACE III) test. Results. The prevalence of CI was 33% in patients and 27% in the control group and was not statistically significant. A higher prevalence of CI was found in subjects aged ≥65 years old than in those <65years old (p = 0.02), but only in the control group. The prevalence of CI in PD patients over and under 65 years of age did not differ statistically significantly (p = 0.12). Memory and verbal fluency were the most affected cognitive domain in PD patients with CI (p = 0.00, p = 0.04, respectively). There was a significant correlation between higher-educated PD patients and the ACE III test results. The duration of dialysis did not affect the results of the cognitive screening test. Conclusion. Cognitive impairment is a growing problem in the course of chronic kidney disease and dialysis therapy. It seems that cognitive problems may occur in patients undergoing peritoneal dialysis at a younger age than in the general population with particularly affected memory and verbal fluency. Higher-educated patients score better on the cognitive screening test