OBJECTIVES: The aims of this study is to investigate the capability of random walks as knee cartilage segmentation method.
METHODS: Experts would scribble on knee cartilage image to initialize random walks segmentation. Then, reproducibility of the method is assessed against manual segmentation by using Dice Similarity Index. The evaluation consists of normal cartilage and diseased cartilage sections which is divided into whole and single cartilage categories.
RESULTS: A total of 15 normal images and 10 osteoarthritic images were included. The results showed that random walks method has demonstrated high reproducibility in both normal cartilage (observer 1: 0.83±0.028 and observer 2: 0.82±0.026) and osteoarthritic cartilage (observer 1: 0.80±0.069 and observer 2: 0.83±0.029). Besides, results from both experts were found to be consistent with each other, suggesting the inter-observer variation is insignificant (Normal: P=0.21; Diseased: P=0.15).
CONCLUSION: The proposed segmentation model has overcame technical problems reported by existing semi-automated techniques and demonstrated highly reproducible and consistent results against manual segmentation method.
METHODS: Knee image is first oversegmented to produce homogeneous superpixels. Then, a ranking model is developed to rank the superpixels according to their affinities to standard priors, wherein background superpixels would have lower ranking values. Finally, seed labels are generated on the background superpixel using Fuzzy C-Means method.
RESULTS: SAGE has achieved better interobserver DSCs of 0.94 ± 0.029 and 0.93 ± 0.035 in healthy and OA knee segmentation, respectively. Good segmentation performance has been reported in femoral (Healthy: 0.94 ± 0.036 and OA: 0.93 ± 0.034), tibial (Healthy: 0.91 ± 0.079 and OA: 0.88 ± 0.095) and patellar (Healthy: 0.88 ± 0.10 and OA: 0.84 ± 0.094) cartilage segmentation. Besides, SAGE has demonstrated greater mean readers' time of 80 ± 19 s and 80 ± 27 s in healthy and OA knee segmentation, respectively.
CONCLUSIONS: SAGE enhances the efficiency of segmentation process and attains satisfactory segmentation performance compared to manual and random walks segmentation. Future works should validate SAGE on progressive image data cohort using OA biomarkers.
BACKGROUND: Channa striatus, also known as haruan, is a fresh water snakehead fish consumed in many parts of Southeast Asia. Channa striatus is also normally consumed by women postpartum to promote wound healing as well as to reduce post-operative pain.
METHODOLOGY: This study is a randomised, double blind, placebo-controlled study conducted in women after Lower Segment Caesarean Section (LSCS). Subjects were randomised to either a Channa striatus or a placebo group and were given a daily dosage of 500 mg of Channa striatus extract or 500 mg maltodextrin, respectively, for six weeks post LSCS. The anteroposterior measurements of the uterus in the longitudinal and oblique transverse planes, and the pulsatility index (PI) and resistive index (RI) of the uterine and superficial skin wound arteries were assessed using pelvic Gray-scale ultrasound and Doppler ultrasound at baseline (Day 3) and at two weeks, four weeks and six weeks post-operatively.
RESULTS: Sixty-six subjects were randomised into the study with 33 in the Channa striatus group and 33 in the placebo group. No significant differences were detected in terms of the pulsatility index (PI) and the resistive index (RI) of the uterine and superficial skin wound arteries between the Channa striatus and placebo groups. However, in the Channa striatus group, the AP measurements of the uterus on the longitudinal and oblique transverse planes were significantly lower compared to the placebo group (p<0.05 and p<0.001, respectively).
CONCLUSION: Daily intake of Channa striatus extract results in marked differences compared to placebo in terms of uterine involution and recovery in women post LSCS.
TRIAL REGISTRATION: www.isrctn.com 11960786.