As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper focuses on the research of medical image segmentation based on deep learning. First, the basic ideas and characteristics of medical image segmentation based on deep learning are introduced. By explaining its research status and summarizing the three main methods of medical image segmentation and their own limitations, the future development direction is expanded. Based on the discussion of different pathological tissues and organs, the specificity between them and their classic segmentation algorithms are summarized. Despite the great achievements of medical image segmentation in recent years, medical image segmentation based on deep learning has still encountered difficulties in research. For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low. The inaccurate segmentation results are unable to meet the actual clinical requirements. Aiming at the above problems, a comprehensive review of current medical image segmentation methods based on deep learning is provided to help researchers solve existing problems.

PurposeTo report the 5-year follow-up results of a randomized controlled trial comparing bipolar transurethral resection of the prostate (TURP) with standard monopolar TURP for the treatment of benign prostatic obstruction (BPO).Materials and MethodsA total of 220 patients were randomized to bipolar plasmakinetic TURP (PK-TURP) or monopolar TURP (M-TURP). Catheterization time was the primary endpoint of this study. Secondary outcomes included operation time, hospital stay, as well as decline in postoperative serum sodium and hemoglobin levels. All patients were assessed preoperatively and followed-up at 1, 6, 12, 24, 36, 48, and 60 months postoperatively. Parameters assessed included quality of life, transrectal ultrasound, serum prostate-specific antigen level, postvoid residual urine volume, maximum urinary flow rates (Qmax), and International Prostate Symptom Score. Patient baseline characteristics, perioperative data including complications, and postoperative outcomes were compared. Complication occurrence was graded according to the modified Clavien classification system.ResultsPK-TURP was significantly superior to M-TURP in terms of operation time, intraoperative irrigation volume, resected tissue weight, decreases in hemoglobin and sodium, postoperative irrigation volume and time, catheterization time, and hospital stay. At 5 years postoperatively, efficacy was comparable between arms. No differences were detected in safety outcomes except that the clot retention rate was significantly greater after M-TURP.ConclusionOur results indicate that PK-TURP is equally as effective in the treatment of BPO, but has a more favorable safety profile in comparison to M-TURP. The clinical efficacy of PK-TURP is long-lasting and comparable with M-TURP.

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In this paper, the discontinuous projection-based adaptive robust control (ARC) approach is extended to a class of nonlinear systems subjected to parametric uncertainties as well as all three types of nonlinear uncertainties-uncertainties could be state-dependent, time-dependent, and/or dynamic. Departing from the existing robust adaptive control approach, the proposed approach differentiates between dynamic uncertainties with and without known structural information. Specifically, adaptive robust observers are constructed to eliminate the effect of dynamic uncertainties with known structural information for an improved steady-state output tracking performance-asymptotic output tracking is achieved when the system is subjected to parametric uncertainties and dynamic uncertainties with known structural information only. In addition, dynamic normalization signals are introduced to construct ARC laws to deal with other uncertainties including dynamic uncertainties without known structural information not only for global stability but also for a guaranteed robust performance in general.

BackgroundGrape seed proanthocyanidin extract (GSPE) has been extensively reported to possess a wide range of beneficial properties in multiple tissue damage. Previous studies have shown that exhaustive exercise-induced fatigue associates with oxidative stress injury, inflammatory response, and mitochondrial dysfunction.ObjectiveThe aim of this study is to investigate the anti-fatigue effects of GSPE in mice and explore its possible underlying mechanism.DesignThe mouse model of exhaustive exercise-induced fatigue was established by using the forced swimming test, and GSPE was orally treated for successive 28 days at 0, 1, 50 and 100 mg/kg/day of body weight, designated the control, GSPE-L, GSPE-M and GSPE-H groups, respectively.ResultsThe presented results showed that treatment of GSPE at a dose of 50 and 100 mg/kg/day of body weight significantly relieved exhaustive exercise-induced fatigue, indicated by increasing the forced swimming time. In addition, treatment of GSPE significantly improved the creatine phosphokinase and lactic dehydrogenase, as well as lactic acid level in exhaustive swimming. For underlying mechanisms, treatment of GSPE had anti-fatigue effects by promoting antioxidant ability and resisting oxidative effect, as represented by increased total antioxidative capability levels, enhanced superoxide dismutase and catalase activities, and ameliorated malondialdehyde levels. Furthermore, treatment of GSPE significantly inhibited the activity of tumor necrosis factor-α and interleukin-1β, which suggested that its protective effects on exhaustive exercise-induced fatigue may be attributed to inhibition of inflammatory response. Last but not the least, treatment of GSPE significantly improved succinate dehydrogenase and Na+-K+-ATPase levels to enhance mitochondrial function during exhaustive swimming-induced fatigue.ConclusionsThese results proved that treatment of GSPE possessed the beneficial properties of anti-inflammatory, antioxidant, and mitochondrial protection to improve exhaustive exercise, which suggested that GSPE could be used as an effective functional food to delay fatigue.

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