Automatic detection of breast lesions in automated 3D breast ultrasound with cross-organ transfer learning

Background Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications,particularly in visual recognition tasks such as image and video analyses.There is a growing interest in applying this technology to diverse applications in medical image analysis.Automated three dimensional Breast Ultrasound is a vital tool for detecting breast cancer,and computer-assisted diagnosis software,developed based on deep learning,can effectively assist radiologists in diagnosis.However,the network model is prone to overfitting during training,owing to challenges such as insufficient training data.This study attempts to solve the problem caused by small datasets and improve model detection performance.Methods We propose a breast cancer detection framework based on deep learning(a transfer learning method based on cross-organ cancer detection)and a contrastive learning method based on breast imaging reporting and data systems(BI-RADS).Results When using cross organ transfer learning and BIRADS based contrastive learning,the average sensitivity of the model increased by a maximum of 16.05%.Conclusion Our experiments have demonstrated that the parameters and experiences of cross-organ cancer detection can be mutually referenced,and contrastive learning method based on BI-RADS can improve the detection performance of the model.

Flotation behaviors of chalcopyrite and galena using ferrate(Ⅵ) as a depressant

This paper investigated the effects of potassium ferrate(PF)on the flotation performances of chalcopyrite and galena.The flotation results showed that PF obviously depressed galena,but had little effects on the floatability of chalcopyrite within pH range of 4.0–12.0.Zeta potential tests showed that the addition of PF induced the formation of more amounts of hydrophilic species on the surface of galena under an alkaline environment.Industrial grade O-isopropyl-N-ethyl thionocarbamate(IPETC)chemically adsorbed on the surface of the PF-treated chalcopyrite and galena after its addition.Contact angle measurements showed that with the addition of PF,the contact angle of the galena surface significantly decreased compared with the chalcopyrite surface.Localized electrochemical impedance spectroscopy(LEIS)tests showed that the addition of PF increased the impedance of the galena surface.X-ray photoelectron spectroscopy(XPS)analyses revealed that the formation of hydrophilic species,namely lead sulfite,lead hydroxide and ferric hydroxide,on the galena surface,decreased its floatability in the presence of PF,while the formation of hydrophobic species,namely copper disulfide and elemental sulfur,on the chalcopyrite surface,maintained its floatability.Finally,a descriptive model for the reaction of PF with chalcopyrite and galena was proposed.