Spine muscle auto segmentation techniques in MRI imaging: a systematic review.

Background: The accurate segmentation of spine muscles plays a crucial role in analyzing musculoskeletal disorders and designing effective rehabilitation strategies. Various imaging techniques such as MRI have been utilized to acquire muscle images, but the segmentation process remains complex and challenging due to the inherent complexity and variability of muscle structures. In this systematic review, we investigate and evaluate methods for automatic segmentation of spinal muscles.

Assessment of Automated Identification of Phases in Videos of Total Hip Arthroplasty Using Deep Learning Techniques.

Background: As the population ages, the rates of hip diseases and fragility fractures are increasing, making total hip arthroplasty (THA) one of the best methods for treating elderly patients. With the increasing number of THA surgeries and diverse surgical methods, there is a need for standard evaluation protocols. This study aimed to use deep learning algorithms to classify THA videos and evaluate the accuracy of the labelling of these videos.

Accelerometer-derived physical activity analysis of elderly osteoarthritis patients.

Background: Because disability in Osteoarthritis (OA) may change physical activity (PA), which might affect the disease progression, it is important to measure a patient's daily PA to study the relationship between a patient's PA and disease progression.

Objective: The objective of the present study was to investigate the relationship between PA and patients with OA and people without OA using data from the Korea National Health and Nutrition Examination Survey (KNHANES).

Methods: Demographic study was conducted to obtain data of comorbidities of participants.

Correlation between Harris hip score and gait analysis through artificial intelligence pose estimation in patients after total hip arthroplasty.

Background: Recently, open pose estimation using artificial intelligence (AI) has enabled the analysis of time series of human movements through digital video inputs. Analyzing a person's actual movement as a digitized image would give objectivity in evaluating a person's physical function. In the present study, we investigated the relationship of AI camera-based open pose estimation with Harris Hip Score (HHS) developed for patient-reported outcome (PRO) of hip joint function.

Comprehensive Comparative Analysis of Local False Discovery Rate Control Methods.

Due to the advance in technology, the type of data is getting more complicated and large-scale. To analyze such complex data, more advanced technique is required. In case of omics data from two different groups, it is interesting to find significant biomarkers between two groups while controlling error rate such as false discovery rate (FDR).