電腦輔助分類女性禿髮嚴重程度之影像處理分析系統

Abstract

傳統的女性禿髮嚴重程度判定，是根據文獻上所定義的標準女性禿髮樣式，最常用的判定樣式叫做Ludwig和Savin等級，雖然這些樣式已經廣為普遍使用，但是因為判定的方式都是診斷者對照樣式圖，之後根據自己主觀肉眼判斷，所以往往判定結果因人而異，所以本研究就是希望藉由電腦輔助診斷，開發一套系統可以客觀的分析，且希望精確度可以更高。 本研究使用的方法是經由禿髮影像的分析，來診斷禿髮的嚴重程度，所以首先會對病人進行拍照，將拍照的影像做影像處理。處理最重要的步驟就是將禿髮的區域給分割出來，本研究使用等位函數法的方式自動將禿髮區域給分割出來，避免掉主觀判斷，之後將分割出來的禿髮區域擷取出兩個特徵值，分別為禿髮區域寬度和頭髮稀疏帶面積，其中頭髮稀疏帶是說在禿髮區域外圍，往往還有一些有頭髮但是比較稀疏一點的區域。用這兩個特徵值和使用支持向量機分類器我們進行女性禿髮程度的評估。 本研究總共有44個禿髮病人影像和1個正常人的影像，拍照的原則是：病人不動的情況下連拍兩張影像，然後頭髮再重新梳理過之後再拍兩張照片。病人不動拍兩張是因為相機所拍的影像會有亮度差異，所以連續拍兩張的影像可以拿來做比較，這樣就能分析影像亮度不同對系統造成的差異。頭髮重新梳理過之後再拍的影像是為了分析頭髮梳理方式對系統的影響。本研究最後經由兩個特徵值:禿髮區域寬度和頭髮稀疏帶面積，在禿髮程度Ludwig等級二以內的病人成功的分出六類，最後在分析亮度影響和頭髮梳理的影響下，誤差比例約為一成多。

Traditional methods for grading stages of female alopecia, as described in published references, use scales such as the Ludwig scale or the Savin scale. Although these scales are widely accepted, they are often based on subjective evaluation of an investigator matching a subject with pictures on a pictorial classification scale. Consistency between investigators is low. With the assistance of computers, this study aimed to create a system that objectively analyzes alopecia severity in the hopes of increasing diagnostic accuracy. The purpose of this study was to grade alopecia through the analysis of an image containing a subject’s balding pattern. In order to achieve that, a photograph of the subject was obtained and the image processed. The most important step was segmenting the region of baldness. This study used the level set methods for segmenting region of baldness, thus eliminating subjective evaluation. Then, using this identified region, two features were extracted. One was the width of the bald region; the second was the area of decreased hair density, which was defined as region around the bald patches that still contain hair, albeit much thinner. Evaluation of female alopecia was carried out using the two features and support vector machines. This study included 44 patients suffering from alopecia and 1 normal subject. The standard procedure for acquiring the images was taking two consecutive photographs while the subject stayed immobile. After grooming the hair, the process was repeated again. The rationale behind two consecutive photographs was that differences in brightness may affect the final result of the analysis, so the two sets were used for comparison. This way, the effects can be elucidated. The reason for grooming and repeating the procedure was to see if and how different hairstyles affected the results of the system. Using the features of the width of the bald region and area of decreased hair density, patients rated as type 2 or under on the Lugwig scale were successfully divided into six categories. When taking into account changes in brightness and effect of grooming, the percentage of error is around 15%.