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لوکوویت: یک مدل کارآمد مبتنی بر ترانسفورمر بینایی برای طبقهبندی خودکار لکوسیتها | ||
مجله مهندسی برق دانشگاه تبریز | ||
دوره 54، شماره 3 - شماره پیاپی 109، آذر 1403، صفحه 335-346 اصل مقاله (1.05 M) | ||
نوع مقاله: علمی-پژوهشی | ||
شناسه دیجیتال (DOI): 10.22034/tjee.2024.58463.4727 | ||
نویسندگان | ||
زهرا اصغرزاده؛ سینا شامخی* | ||
گروه بیوالکتریک، دانشکده مهندسی پزشکی، دانشگاه صنعتی سهند، تبریز، ایران | ||
چکیده | ||
شناسایی و ارزیابی لکوسیتها برای ارزیابی کیفیت سیستم ایمنی انسان مهم است. با این حال، تجزیه و تحلیل اسمیر خون به تخصص پاتولوژیست بستگی دارد. روش دستی برای تجزیه و تحلیل و طبقه بندی گلوبولهای سفید ها پرهزینه و زمانبر است و می تواند منجر به خطا در تشخیص شود. اکثر روشهای یادگیری عمیق از مدل های مبتنی بر CNN برای طبقه بندی گلبولهای سفید استفاده میکنند. این مقاله استفاده از یک شبکه مبتنی بر ViT را برای طبقهبندی لکوسیتها در نمونه خون مورد بحث قرار میدهد. مجموعه داده مورد استفاده در این مقاله شامل 352 تصویر با اندازه 320 در 240 است که از طریق روشهایی برای ایجاد یک مجموعه داده متعادل از 12444 تصویر دادهافزایی شده است. سپس دادههای افزایشیافته برای آموزش معماری مبتنی بر ViT برای طبقهبندی انواع مختلف گلبولهای سفید مورد استفاده قرار گرفته است. دراولین مرحلهاز روش پیشنهادی، یک توکنایزر کانولوشن برای استخراج پچ تصاویر اعمال شده است. این پچها فلت شده و به عنوان ورودی برای ساختار مبتنی بر ViT برای شناسایی زیر کلاسها در مرحله دوم استفاده شدهاند. نتایج بهدستآمده با استفاده از لوکوویت نشان میدهد صحت شبکه پیشنهادی 99.04 درصد است که نسبت به شبکههای پیشرفته برتری دارد. | ||
کلیدواژهها | ||
گلبول های سفید؛ طبقه بندی تصویر؛ یادگیری عمیق؛ شبکه عصبی کانولوشن؛ ترانسفورمر بینایی | ||
مراجع | ||
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آمار تعداد مشاهده مقاله: 218 تعداد دریافت فایل اصل مقاله: 62 |