Existing classification methods for myositis ultrasound images have problems of poor classification performance or high computational cost. Motivated by this difficulty, a lightweight neural network based on a soft threshold attention mechanism is proposed to cater for a better IIMs classification. The proposed network was constructed by alternately using depthwise separable convolution (DSC) and conventional convolution (CConv). Moreover, a soft threshold attention mechanism was leveraged to enhance the extraction capabilities of key features. Compared with the current dual-branch feature fusion myositis classification network with the highest classification accuracy, the classification accuracy of the network proposed in this paper increased by 5.9%, reaching 96.1%, and its computational complexity was only 0.25% of the existing method. The obtained results support that the proposed method can provide physicians with more accurate classification results at a lower computational cost, thereby greatly assisting them in their clinical diagnosis.
ObjectiveTo explore the relation between ultrasound images of endometriosis and its clinical symptoms.
MethodsChoosing clinical data of 300 patients with endometriosis pathologically diagnosed between January 2009 and January 2014, we retrospectively analyzed ultrasound images and clinical symptoms, using Chisquare test for statistical analysis, and the index P<0.05 was statistically significant.
ResultsIn patients with big endometriosis' nidus, the menstrual quantity increased, menstrual cycle prolonged, the incidence of abnormally vaginal bleeding was high (χ2=11.749, P=0.001; χ2=4.847, P=0.028; χ2=5.686, P=0.017). In patients whose endometriosis were located in posterior uterine wall, the menstrual quantity increased, and the incidence of abnormally vaginal bleeding was high (χ2=5.188, P=0.023; χ2=49.691, P<0.001). The size of endometriosis' nidus had nothing to do with dysmenorrhea, constipation and frequent micturition (P>0.05). The position of endometriosis' nidus had nothing to do with menostaxis, dysmenorrhea, constipation and frequent micturition (P>0.05).
ConclusionThe size of endometriosis' nidus has a connection with the clinical symptoms of menorrhea, menostaxis and abnormally vaginal bleeding; the position of endometriosis' nidus has a connection with the clinical symptoms of menorrhea and abnormally vaginal bleeding. The results of ultrasonography should be combined with clinical symptoms in diagnosing endometriosis, avoiding missed-diagnosis and misdiagnosis.
