[Development and Application of Deep Learning-Based Model for Quality Control of Children Pelvic X-Ray Images].

Objective: A deep learning-based method for evaluating the quality of pediatric pelvic X-ray images is proposed to construct a diagnostic model and verify its clinical feasibility.

Methods: Three thousand two hundred and forty-seven children with anteroposteric pelvic radiographs are retrospectively collected and randomly divided into training datasets, validation datasets and test datasets. Artificial intelligence model is conducted to evaluate the reliability of quality control model.

[Application of Deep Learning to Diagnose and Classify Adolescent Idiopathic Scoliosis].

A deep learning-based model for automatic diagnosis and classification of adolescent idiopathic scoliosis has been constructed. This model mainly included key points detection and Cobb angle measurement. 748 full-length standing spinal X-ray images were retrospectively collected, of which 602 images were used to train and validate the model, and 146 images were used to test the model performance.

Clinical reliability and validity of a video-based markerless gait evaluation method.

Objective: To explore the reliability and validity of gait parameters obtained from gait assessment system software employing a human posture estimation algorithm based on markerless videos of children walking in clinical practice.

Methods: Eighteen typical developmental (TD) children and ten children with developmental dysplasia of the hip (DDH) were recruited to walk along a designated sidewalk at a comfortable walking speed. A 3-dimensional gait analysis (3D GA) and a 2-dimensional markerless (2D ML) gait evaluation system were used to extract the gait kinematics parameters twice at an interval of 2 h.

A novel approach for screening standard anteroposterior pelvic radiographs in children.

Unlabelled: Anteroposterior pelvic radiography is the first-line imaging modality for diagnosing developmental dysplasia of the hip (DDH). Nonstandard radiographs with pelvic malposition make the correct diagnosis of DDH challenging. However, as the only method available for screening standard pelvic radiographs, traditional manual assessment is relatively laborious and potentially erroneous.

Clinical thought-based software for diagnosing developmental dysplasia of the hip on pediatric pelvic radiographs.

Background: The common methods of radiographic diagnosis of developmental dysplasia of the hip (DDH) include measuring hip parameters and quantifying the degree of hip dislocation. However, clinical thought-based analysis of hip parameters may be a more effective way to achieve expert-like diagnoses of DDH. This study aims to develop a diagnostic strategy-based software for pediatric DDH and validate its clinical feasibility.

A facile method to modify polypropylene membrane by polydopamine coating via inkjet printing technique for superior performance.

Membrane surface functionalization based on mussel-inspired polydopamine (PDA) deposition for enhancing antifouling ability has attracted considerable attention. However, high cost of dopamine (DA) and long-time of reaction during self-polymerization of DA in aqueous solution remain the major problems impeding its practical application. This study provided a first report on a low-cost and facile membrane modification approach based on inkjet printing of DA and sodium periodate (SP) to rapidly deposit PDA on polypropylene (PP) membrane.