1.Clinical Observation on Treatment of Spastic Cerebral Palsy with Tuina plus Music Therapy
Meimei MA ; Zhenhuan LIU ; Yong ZHAO ; Guanjun LUO ; Nuo LI ; Wenjian ZHAO ; Ruiping WAN ; Chouping HAN
Journal of Acupuncture and Tuina Science 2009;7(4):213-217
Objective: To observe the effect oftuina plus music therapy on range of motion of ankle joints and muscle spasm of lower limbs in children with spastic cerebral palsy. Method:All of 286 cases that conformed to the diagnostic criteria of infantile cerebral palsy were treated with 7 types of tuina manipulations respectively to unblock the Governor Vessel, reinforce the kidney and strengthen the spleen, pinch along the spine, stimulate specific foot-reflex area and different spinal segments, accelerate recovery of muscle strength and increase joint range of motion, 25-30 rain each treatment, once or twice a day, 30 d constitute a course of treatment.After this, the efficacy on femoral medial adduction and dorsiflexion angle and composite spasticity score (CSS) was evaluated. Result: The statistical analysis showed significant differences in dorsiflexion and femoral medial adduction angle and CCS scores (P<0.01) after the treatments. Conclusion: Tuina plus music therapy can lubricate the joints, relax contraction of tendons, alleviate muscle spasm and improve scissors and toe-walking gaits, thereby benefiting the gross motor function of infants in sitting, kneeling, standing and walking.
2.A novel ROI extracting technique based on wavelet transform for the detection of micro-calcifications in mammograms.
Shunan LI ; Baikun WAN ; Zhenhe MA ; Ruiping WANG
Journal of Biomedical Engineering 2005;22(2):360-362
In order to preprocess mammograms for diagnosing the early cases of breast cancer and improving the computational efficiency in the computer-aided detection of micro-calcifications in mammograms, we have advanced a novel processing technique for the extraction of micro-calcification region of interest (MROI). The proposed method is based on a three-step procedure: (1) the mammogram is divided into sub-images of the same size; (2) the wavelet multi-resolution method is conducted on the sub-images, and the parameters related to wavelet transform and threshold T are discussed according to rho; (3) the classification of sub-images is determined by T. It is tested with 20 mammograms and the results show that the method can achieve a true positive rate as high as 89.7% with a false positive rate as low as 2.1%.
Breast Diseases
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diagnostic imaging
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pathology
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Breast Neoplasms
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diagnostic imaging
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pathology
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Calcinosis
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diagnostic imaging
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Diagnosis, Computer-Assisted
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Humans
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Mammography