Artificial Neural Networks and K-Nearest Neighbors for the detection of kidney stones from CT-scan images : A comparative study

  • سال انتشار: 1401
  • محل انتشار: نهمین کنفرانس بین المللی مهندسی برق ،الکترونیک و شبکه های هوشمند
  • کد COI اختصاصی: EESCONF09_018
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 263
دانلود فایل این مقاله

نویسندگان

Seyed Pouya Musavi Ghasemi

Seraj Higher Education Institute-Tabriz

Faramarz Ariyani Shirvanehdeh

Seraj Higher Education Institute-Tabriz

Naser Nasirzadeh Azizkandi

Seraj Higher Education Institute-Tabriz

چکیده

Chronic kidney disease is a progressive disease associated with a high risk of cardiovascular disease, high mortality and health care costs. Therefore, early diagnosis of the disease is very important to control its consequences. Kidney stones are hard sediments that are often formed due to the increase in the concentration of solutes and salts in the urine. Medical imaging for segmentation of kidney stones is one of the important research topics in recent years. To diagnose kidney stones, the noise of the images and the contrast should be reduced so that the classification and division of the kidney can be done easily. First, we used image pre-processing techniques including noise removal, smoothing, sharpening, and contrast enhacement, then the features were extracted using the gray level co-occurrence matrix, after that the optimal features were selected. In this research, our purpose was to use artificial neural networks along with the Bayesian regularization training algorithm and the K-nearest neighbors algorithm for data classification, where the selected features were considered as input and labels as targets and Finally, according to the results obtained from both methods, the artificial neural networks had a better performance with a ۹۹/۰۷% than K-nearest neighbors algorithm with a ۹۰%.

کلیدواژه ها

Chronic kidney disease, kidney stones, artificial neural networks, k-nearest neighbors, CT scan image, classification

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.