A two-dimensional video based quantification method and clinical application research of motion disorders / 生物医学工程学杂志

The increasing prevalence of the aging population, and inadequate and uneven distribution of medical resources, have led to a growing demand for telemedicine services. Gait disturbance is a primary symptom of neurological disorders such as Parkinson's disease (PD). This study proposed a novel approach for the quantitative assessment and analysis of gait disturbance from two-dimensional (2D) videos captured using smartphones. The approach used a convolutional pose machine to extract human body joints and a gait phase segmentation algorithm based on node motion characteristics to identify the gait phase. Moreover, it extracted features of the upper and lower limbs. A height ratio-based spatial feature extraction method was proposed that effectively captures spatial information. The proposed method underwent validation via error analysis, correction compensation, and accuracy verification using the motion capture system. Specifically, the proposed method achieved an extracted step length error of less than 3 cm. The proposed method underwent clinical validation, recruiting 64 patients with Parkinson's disease and 46 healthy controls of the same age group. Various gait indicators were statistically analyzed using three classic classification methods, with the random forest method achieving a classification accuracy of 91%. This method provides an objective, convenient, and intelligent solution for telemedicine focused on movement disorders in neurological diseases.

A generative adversarial network-based unsupervised domain adaptation method for magnetic resonance image segmentation / 生物医学工程学杂志

Intelligent medical image segmentation methods have been rapidly developed and applied, while a significant challenge is domain shift. That is, the segmentation performance degrades due to distribution differences between the source domain and the target domain. This paper proposed an unsupervised end-to-end domain adaptation medical image segmentation method based on the generative adversarial network (GAN). A network training and adjustment model was designed, including segmentation and discriminant networks. In the segmentation network, the residual module was used as the basic module to increase feature reusability and reduce model optimization difficulty. Further, it learned cross-domain features at the image feature level with the help of the discriminant network and a combination of segmentation loss with adversarial loss. The discriminant network took the convolutional neural network and used the labels from the source domain, to distinguish whether the segmentation result of the generated network is from the source domain or the target domain. The whole training process was unsupervised. The proposed method was tested with experiments on a public dataset of knee magnetic resonance (MR) images and the clinical dataset from our cooperative hospital. With our method, the mean Dice similarity coefficient (DSC) of segmentation results increased by 2.52% and 6.10% to the classical feature level and image level domain adaptive method. The proposed method effectively improves the domain adaptive ability of the segmentation method, significantly improves the segmentation accuracy of the tibia and femur, and can better solve the domain transfer problem in MR image segmentation.

A comparison of the Yang-Monti and appendix in the practice of the continent urinary diversion / 中华泌尿外科杂志

Objective To compare the outcomes of Yang-Monti channels and appendix in the practice of catheterizable continent urinary conduits.Methods Retrospective analyses were conducted in 27 cases with neurogenic bladder from July 2009 to December 2015,including 8 male and 19 female patients whose average age at surgery was 7.6 years old (range:1.5-16 years).The average bladder volume is (203.8 ± 126.0) ml.The bladder compliance values of 24 cases are lower than 20 ml/cm H2O.Seventeen cases had urinary infection combined with fever before surgery,while 6 cases had stress urinary incontinence and 17 cases had dysuria.Seven cases including 2 male patients underwent urinary diversion with YangMonti channels (YM group) and the average age at surgery for patients was 6.7 years old (range:4-16years).Twenty cases including 6 male patients underwent urinary diversion with appendix (AP group) and the average age at surgery for patients was 8.0 years old(range:1.5-14 years).The 3-day urinary diaries were collected in all cases including their records of average catheterization interval,average catheterization volume,stoma stenosis and stoma leakage.The data between the two groups was compared and the statistical analysis was performed.Results Of the 7 patients undergoing Yang-Monti channels,2 cases underwent open surgery and 5 cases underwent laparoscopic surgery in which 2 cases transferred to open surgery.The stoma stenosis occurred in 1 case and the stoma leakage occurred in 1 case.The average catheterization volumc is (239.3 ± 76.2) ml and the average catheterization interval is (2.8 ± 0.9) h.Six patients in the group were followed up less than 3 years,of which the average catheterization interval is (2.6 ± 0.8) h.Of the 20 patients undergoing appendix channels,3 cases underwent open surgery and 17 cases underwent laparoscopic surgery in which 1 case transferred to open surgery.The stoma stenosis occurred in 1 case and the stoma leakage occurred in 2 cases.The average catheterization Volumee is (257.0 ± 67.4) ml and the average catheterization interval is (3.9 ± 0.9)h.Six patients in the group were followed up less than 3 years,of which the average catheterization interval is(3.5 ± 1.0) h.There was no difference in stoma stenosis and stoma leakage and average catheterization volume between the two groups (P ＞ 0.05).There was no difference in average catheterization interval between the patients of two groups who were followed up less than 3 years (P ＞ 0.05).Conclusions Yang-Monti conduits are durable and reliable,which was similar with appendix conduits.