A Quantitative Study on Acupuncture Effects for Fighting Migraine Using SPECT Images
The aim of this paper is to quantitatively determine whether acupuncture, applied under real conditions of clinical practice in the area of primary healthcare, is effective for fighting migraine. This is done by evaluating SPECT images of migraine patients’ brain in a context of image classification. Two different groups of patients are randomly collected and received verum and sham acupuncture, respectively. In order to make the image processing computationally efficient and solve the small sample size problem, an initial feature extraction step based on Principal Component Analysis is performed on the images. Differences among features extracted from pre– and post–acupuncture scans are quantified by means of Support Vector Machines for verum and sham modalities, and statistically reinforced by carrying out a statistical t–test. The conclusions of this work point at acupuncture as an effective method to fight migraine.
KeywordsSPECT acupuncture migraine PCA SVM class separability
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