利用圆霍夫变换早期检测核性白内障的计算机辅助系统

A. Jagadale, S. S. Sonavane, D.V. Jadav
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引用次数: 9

摘要

世界卫生组织对致盲原因的调查表明,白内障是致盲的主要原因。虽然年龄相关性白内障是最常见的,但由于其出现在未成年人和儿童的双眼,这是一个严重的问题。由于白内障对视力的影响较小,早期发现白内障是一个挑战。三种最常见的白内障类型是核性白内障、皮质性白内障和后囊下白内障。裂隙灯观察与晶状体混浊分类系统(LOCS-III)用于眼科医生的检测和医学诊断。晶状体置换手术是矫正视力最常用的治疗方法。文献综述表明,计算机辅助检测分级的成功和正确性取决于白内障眼图像中晶状体定位的正确性。本文利用眼科医院眼科医生的裂隙灯图像,结合计算机辅助图像处理,对白内障进行早期检测。晶状体检测、晶状体分割、特征提取和分类是白内障早期检测的难点。采用霍夫圆检测变换进行透镜检测,支持向量机进行分类,提高了整体精度。使用统计特征提取和先验训练的支持向量机进行检测和分类。
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Computer Aided System For Early Detection Of Nuclear Cataract Using Circle Hough Transform
Survey done by world health organization for probing causes of blindness indicates that cataract is major cause of blindness. Even age related cataract is most commonly observed, it is serious cause to think because of its appearance in minors and children for both eyes. Detecting cataract at earlier stage is challenge as it has less affecting vision. The three most general types of cataract are nuclear cataract, cortical cataract and post subcapsular cataract. Slit lamp observation with lens opacity classification system (LOCS-III) is used for detection and medical diagnosis by ophthalmologists. Lens replacement surgery is most common treatment suggested on cataract for correcting vision. Literature survey indicates towards the success and correctness of computer added detection and grading is function of correctness of lens localization from cataract eye image. The work presented in this paper uses slit lamp images from ophthalmologist at eye hospital with computer aided image processing to detect cataract at earlier stage. The challenge of detection of cataract at earlier stage is attended in steps like lens detection, lens segmentation, feature extraction and categorization. The overall accuracy is enhanced by use of Hough circle detection transform for lens detection and support vector machine for categorization. The detection and categorization is performed using statistical feature extraction with prior trained support vector machine.
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