Real-time evaluation of breast self-examination using computer vision

Practice and Barriers toward Breast Self-Examination among Palestinian Women in Gaza City, Palestine

Breast self-examination (BSE) is one of many first-line screening practices aimed at early detection and prevention of fatal outcomes of breast cancer. The present study aimed to identify Palestinian women's practices, awareness, and barriers to BSE. Using descriptive-analytical methods, a previously validated questionnaire was administered to a conveniently selected sample of women. The study was conducted among women who visited primary health clinics (PHCs) in Gaza City. A total of 390 participants who met the selection criteria answered the self-administered questionnaires. We used SPSS version 24.0 to analyze the data. The findings suggest that the practice of BSE among women in Gaza is low, with only 40% of the study participants reporting that they never practiced BSE before, even though 76.7% reported that they were aware of BSE. In general, the main barriers to BSE practices were that participants had wrong perceptions and lacked knowledge about BSE. Others also reported fear of detecting breast cancer as a barrier. The practice of BSE among Palestinian women in the Gaza Strip is low and marred with trivial issues as barriers that could be eliminated with dedicated and extensive educational campaigns in the area.

Estimation of Object Elasticity by Capturing Fingernail Images During Haptic Palpation

In this study, we present a system that performs natural-touch-based elasticity estimation for an object by using a depth camera. To estimate elasticity, which is defined as an object's Young's modulus, a strain-stress curve is obtained from fingernail images during haptic palpation. From a color image, the proposed system detects a fingernail and extracts 10 feature values related to the contact force; then, it estimates the force using a multiple regression model. Deformation of the object was estimated from the finger's three-dimensional position obtained from both color and depth images. Then, a strain-stress curve was determined using the force and deformation data. Evaluation experiments were designed to obtain the strain-stress curves of five objects from 10 participants; then, the estimation performance was investigated. The results show that the reliable range of sensing was within Young's modulus values of 0.12-5.6 MPa and the precision of the measurement was 55 percent of the estimated elasticity.